Today, AWS announces the expanded availability of OpenAI's GPT-5.4 and GPT-5.5 models, which are now available in the US East (N. Virginia) Region on Amazon Bedrock. With GPT-5.4 and GPT-5.5, you can build generative AI applications across reasoning, coding, computer use, document workflows, and long-running agentic tasks. GPT-5.5 is OpenAI's most capable model, designed for advanced coding, research, analysis, software operation, document workflows, and long-running agentic tasks. It can understand open-ended goals, use tools, reason across longer workflows, navigate ambiguity, and carry complex tasks through to completion with less orchestration. GPT-5.4 brings frontier reasoning, coding, computer use, long-context workflows, and tool use to production applications that interpret context, interact with tools, operate software environments, and verify outputs across multiple steps. Both models support a 272K-token context window, accept text and image input, and are available through the Responses API with support for server-side and client-side tool calling, projects, and response streaming. With this launch, GPT-5.4 and GPT-5.5 are now available in additional AWS Regions. To get started, visit the GPT-5.5 and GPT-5.4 model cards in our documentation.

Amazon OpenSearch Service now supports MCP Apps, bringing observability workflows directly into compatible agentic IDEs such as Claude Desktop and VS Code. With this capability, your AI agent in local environment can investigate incidents using logs, traces, metrics, and alerts stored in OpenSearch domains, collections and Amazon Managed Service for Prometheus. You can easily review and verify the results in interactive MCP App visualizations without leaving your local environment. Each MCP App tool call returns a dual response, a concise text summary for your agent to reason over and an interactive visualization rendered in the same conversation thread for you to review. You can work alongside your observability agent from firing an alert, perform root cause analysis, exploring distributed traces, service maps, PromQL metric charts, and cross-signal correlations all within a single conversation. Available MCP App tools cover log, metrics and trace investigation, service performance, topology, dynamic visualizations, agent health, cluster health, and instrumentation scoring. The OpenSearch MCP app experience is available is available in all AWS Regions where Amazon OpenSearch UI is offered. To get started, follow the instructions in OpenSearch Agentic observability with MCP Apps. To learn more about OpenSearch, visit Amazon OpenSearch Service Developer Guide.

Amazon ECS Managed Daemons now support inter-task visibility and communication, enabling customers to deploy tracing, profiling, and security agents that require access to application processes and shared IPC resources on ECS Managed Instances. With this launch, you can configure two new settings in ECS daemon definitions: pidMode controls whether the daemon can see all processes on the instance, and ipcMode controls whether the daemon shares an IPC namespace with other containers on the instance. Setting either to "shared" grants the daemon access to the respective namespace; the default of "none" keeps daemons isolated from application containers and other tasks. These settings let you run process-aware and IPC-dependent agents as ECS daemons instead of embedding them as sidecars in application task definitions. ECS places exactly one daemon task per managed instance and starts daemons before application tasks, so platform teams can deploy and update agents independently with consistent coverage across all workloads. To get started, register a daemon task definition specifying pidMode or ipcMode set to "shared" using the AWS Console, CLI, CloudFormation, or AWS SDKs, then create or update a daemon with associated ECS Managed Instances capacity providers in your clusters. This feature is now available in all AWS Regions at no additional cost. For more details, refer to our documentation.

Hello, I was wondering which AI certificates would look the best& give me the most ROI in terms of usable skills as a manager/Admin of operations at any company? So far, I've narrowed it down to AI practitioner & Data Engineer. Are these 2 good for what Im looking for or do you recommend a different approach? My background is in administration & innovations/procedures. Note: I have no background in coding/computer science but I do broadly specialize in Data science. submitted by /u/MyMothersFavoriteKid [link] [comments]

Hello all, I've passed quite a bit of AWS certifications this past few months (10 to be exact). I have the certification history in Certmetrics. I have 2 active certifications in another account and have Credly badges for those, but for these ones, I don't. I've tried an account merge, contacted Pearson and opened AWS tickets, but am confused on how this could've happened. Any advice is appreciated! submitted by /u/No-Inflation7960 [link] [comments]

https://preview.redd.it/z7ygya341i6h1.png?width=1695&format=png&auto=webp&s=145b0ee598ff786b603fb95939645272ff007c59 I passed AWS DVA-C02 despite everything going wrong during the exam Before this exam, I had almost no experience with AWS certifications. I spent 36 days preparing for the AWS Certified Developer – Associate (DVA-C02), studying 3–4 hours every day. It was my first AWS certification and also my first time taking an online proctored exam through Pearson VUE. I carefully read all the rules beforehand. I knew phones were not allowed, so I put mine into airplane mode. However, before starting the exam, PearsonVUE required me to take photos of my ID and my room from different angles. To do that, I had to reconnect my phone to Wi-Fi. After taking the photos, I placed the phone behind me and completely forgot about it. The exam started, and my proctor had a strong Indian accent. As a non-native English speaker, I sometimes struggled to understand what he was saying. My English is far from perfect, and the combination of stress and communication difficulties made the beginning of the exam challenging. He asked me to use my laptop camera to show the entire room, which I did, and then the exam finally began. By the second or third question, I was already questioning whether I belonged there at all. The questions weren't impossible, but they were much more detailed and tricky than I expected. I remember thinking, "Maybe I'm not ready. Maybe I should just stop." Fortunately, I didn't. I took a deep breath and kept going. Then another problem started. People began calling my phone. Over and over again. The phone was behind me, ringing throughout the exam. As a non-native English speaker, I already had to spend extra time carefully reading and understanding each question. The constant ringing was incredibly distracting. I wasn't sure whether I was allowed to touch the phone and turn it off. I was afraid the proctor might think I was trying to cheat or access study materials. So I just ignored it and continued. I think it rang at least seven times during the exam. But the worst moment came much later. At around question 50 or 55, my laptop suddenly shut down. My heart stopped. I panicked immediately. The screen went black, and I couldn't understand what had happened. I tried turning the laptop back on, but nothing happened. Then I realized something incredibly stupid: I had forgotten to plug in the charger. Because I was so nervous while setting everything up and showing my room to the proctor, I never connected the power cable. Thankfully, it was a MacBook. After plugging it in, it came back to life after about 30–40 seconds. During those seconds, I was convinced the exam was over. I thought there was no chance I would pass. The laptop had been off, the camera feed was gone, and nobody could see what was happening in my room. When I finally got back into the exam software, I noticed my webcam preview wasn't showing in the corner anymore. At that moment I was almost certain I would be disqualified. Honestly, after that happened, I stopped believing I could pass. I still completed the exam, but mentally I had already accepted failure. The next day I received the email. Pass. I couldn't believe it. After all the difficult questions, the phone ringing constantly, the communication challenges, and even my laptop shutting down in the middle of the exam, I had somehow passed. My takeaway from this experience is simple: Don't give up too early. During the exam I was convinced I was failing. I was wrong. If you're preparing for an AWS certification right now, keep studying, keep pushing, and don't let a few bad moments convince you that it's over. Sometimes everything seems to be going wrong, and you still pass. Good luck to everyone preparing for their AWS exams. You've got this. submitted by /u/Jealous_March8651 [link] [comments]

hello. I recently passed the AWS Certified Solutions Architect - Associate exam with a score of 754. For preparation, I used Tutorials Dojo extensively and consistently scored around 85–90% on the practice exams. However, when I took the actual exam, I felt that the questions were quite different from what I had expected. I thought more questions would be similar to the Tutorials Dojo style, but that wasn't my experience at all. To be clear, I'm not criticizing Tutorials Dojo. It helped me pass the exam, and I believe it's a valuable resource. What I'm curious about is this: for those of you who scored 900+ on the SAA exam, how did you study? Did you use additional resources, gain significant hands-on AWS experience, or focus on something beyond practice exams? I'd love to hear about your study approach and what you think made the difference. submitted by /u/Consistent_Bother_87 [link] [comments]

Hello im a college student from PH. I would like to ask if there's a guide here about the procedures on taking the certification. I plan to take mine on Pearson Vue via Face to Face exam but I don't know if i should but the voucher online or onsite or what are the prerequisites, requirements, any hidden examination fees etc and also what happens after examination and etc. It would really help if someone can provide a end to end guide before and after examination. Thank you so much submitted by /u/Inner_Sport3340 [link] [comments]

Hey everyone, hoping someone has dealt with this before. I passed my AWS Certified Cloud Practitioner back in December 2023 and have a verified Credly badge for it, but my certification has never shown up in my AWS Certification account on Certmetrics. Both my exam history and certification status pages are completely empty. After going back and forth with AWS support (just getting bot responses) I decided to contact Pearson VUE live chat, and that's where things got interesting. Turns out I have multiple Certmetrics accounts all tied to the same email address: Account A - the one I see when I log into cp.certmetrics.com (empty) Account B - the one Pearson VUE confirmed my actual certification is linked to Account C - a third one tied to an old university email Pearson VUE confirmed my cert is under Account B, but when I log into Certmetrics I always land on Account A which is empty. Both accounts are apparently tied to the same email, so I have no idea how two separate accounts got created under the same email address. Has anyone dealt with this before? How did you get AWS to merge the right account into your active one? AWS support keeps sending me the generic self-service merge instructions but those require knowing the email of the second account, which in my case is the same email, so that doesn't help. Any advice appreciated. submitted by /u/NegotiationRound7319 [link] [comments]

Hey all, Due to a time crunch, I need to complete the AWS Certified AI Practitioner exam before june 25th. Do you think this is doable, if so can you all share some relevant tips, notes, and info how long of a prep I would need? For reference, I have full access to Udemy as part of my work benefit, so I would like to mainly use this for prep and for practice questions if possible. Guidance on this would be really appreciated. Thank you! 😀 submitted by /u/jarvisnothere [link] [comments]

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M9g and M9gd instances, powered by AWS Graviton5 processors, are generally available. AWS Graviton5 processors are the fifth generation of custom-designed AWS processors, delivering the best price performance for general purpose workloads running on Amazon EC2. ​​M9g instances serve a broad range of general-purpose workloads including application servers, microservices, gaming, caching, and containers, while also delivering the performance needed for agentic AI use cases like real-time reasoning, code generation, and multi-step orchestration.   ​​M9gd instances offer local NVMe-based SSD block-level storage for customers that require high-speed, low-latency local storage, such as media processing, batch and log processing, and applications that need access to temporary storage including caches and scratch files.​ ​​​M9g and M9gd instances deliver up to 25% better compute performance compared to AWS Graviton4-based M8g and M8gd instances. They are up to 30% faster for databases, up to 35% faster for web applications, and up to 35% faster for machine learning. These instances are built on the sixth-generation AWS Nitro System and are the first to feature the Nitro Isolation Engine, harnessing formal verification to provide mathematical assurance that customer workloads are isolated from each other and AWS operators, pioneering a new standard for mathematically proven cloud security​​. M9g and M9gd instances are available in US East (N. Virginia, Ohio), US West (Oregon), and EU (Frankfurt) regions. M9g and M9gd instances are available for purchase via Savings Plans, On-Demand, Spot instances, Dedicated instances, or Dedicated hosts. Level up your compute with AWS Graviton and get started today.

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) P6-B200 instances accelerated by NVIDIA Blackwell GPUs are available in AWS GovCloud (US-East) Region. These instances offer up to 2x performance compared to P5en instances for AI training and inference. P6-B200 instances feature 8 Blackwell GPUs with 1440 GB of high-bandwidth GPU memory and a 60% increase in GPU memory bandwidth compared to P5en, 5th Generation Intel Xeon processors (Emerald Rapids), and up to 3.2 terabits per second of Elastic Fabric Adapter (EFAv4) networking. P6-B200 instances are powered by the AWS Nitro System, so you can reliably and securely scale AI workloads within Amazon EC2 UltraClusters to tens of thousands of GPUs. P6-B200 instances are now available in p6-b200.48xlarge size in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio), AWS GovCloud (US-West) and AWS GovCloud (US-East) Region. To learn more about P6-B200 instances, visit Amazon EC2 P6 instances.

AWS today announces that AWS Cost and Usage Report 2.0 (CUR 2.0) now supports updates to data table configurations via the AWS Management Console and SDK/CLI. This capability allows customers to modify their existing exports to take advantage of new CUR 2.0 features without having to delete and recreate their exports. Previously, customers configured CUR 2.0 exports with specific table settings — including export content, time granularity, column selection, export format, and destination settings. When AWS introduces new features, such as additional columns and finer row-level granularity, existing export settings intentionally remained unchanged to protect ETL jobs that depended on a stable schema. However, customers who wanted to adopt these new capabilities and were ready for the new schema couldn't simply update their preference in existing export. They had to delete their existing export and create a new one with the new preference. With this launch, customers can update their table configuration directly through the AWS Management Console or SDK/CLI and begin receiving exports with their updated preferences starting from the next scheduled export delivery. To learn more about this feature, see AWS Data Exports and AWS Billing and Cost Management in the AWS Cost Management User Guide.

Just wanted to share my experience in case it helps someone preparing for the exam. Background: I'm a 2nd year Data Science student, so I already have some familiarity with AI/ML concepts. We get 100% discount voucher on behalf of our college so I decided to attempt the exam. My preparation was surprisingly simple: I used only this YouTube playlist from start to finish: https://www.youtube.com/playlist?list=PL7Jj8Ba9Yr6BLf2lS4Nfa2jdl0KpdvqYC No paid courses No paid practice tests No exam dumps No additional study material I focused on understanding the concepts rather than memorizing answers. The exam heavily tests AI fundamentals, Generative AI concepts, responsible AI, common AWS AI services, and practical use cases. My shift had more questions of governance and regulations so prepare that topic thoroughly. Happy to answer any questions about the exam or my preparation strategy. Good luck to everyone preparing! https://preview.redd.it/1qvm0zgr3g6h1.png?width=955&format=png&auto=webp&s=2ad1f194708bb2a5e2775b09943313aba12fbe57 submitted by /u/Alternative-Box3612 [link] [comments]

https://preview.redd.it/4y7jmuqwrf6h1.png?width=1361&format=png&auto=webp&s=a443554ebae2daa96805399b17a3240580d8b364 My first professional certificate! Some comments: I've been working almost daily with the most part of the services required except for some of the more exotic/expensive ones like Direct Connect, Storage Gateway, or S3 Snow. I took notes while listening to Udemy SAP course and taking Udemy and TD test exams. If English is not your native language, make sure to get the +30 extra minutes when booking the exam. Finally, I recommend against drinking as you're not allowed to leave your desk. submitted by /u/sitilge [link] [comments]

Hello im a college student from PH. I would like to ask if there's a guide here about the procedures on taking the certification. I plan to take mine on Pearson Vue via Face to Face exam but I don't know if i should but the voucher online or onsite or what are the prerequisites, requirements, any hidden examination fees etc and also what happens after examination and etc. It would really help if someone can provide a end to end guide before and after examination. Thank you so much submitted by /u/Inner_Sport3340 [link] [comments]

I'm going to attempt cloud practitioner today submitted by /u/Warm-Fail-6628 [link] [comments]

Hi everyone. Just passed the Solutions Architect Professional exam, score 770+. It felt very tough - I walked out genuinely unsure, sitting with a 50/50 feeling the whole time. There were only a few questions closely resembling what I had seen in TD. Most of the content was new to me, not directly repeating what I had studied. That said, the overall style and feel of the questions was similar to the official AWS Skill Builder practice exam and TD - less so to Maarek's practice questions. This time I did not use Neal Davis mock exams (I used them for other certs before). There were 2-3 questions about Bedrock, mostly focused on designing solutions that handle PII or sensitive data. As a non-native speaker I had a 30-minute accommodation, so 210 minutes total. I took one short bathroom break (~3 min) at the 150-minute mark, finished all questions 20 minutes before the end, and used the remaining time reviewing few flagged questions. Prior passed exams: SAA-C02 (2021), DAS-C01 (2023), DEA-C01 (2024) Timeline: - Prep start: March 2026 - Exam: beginning of June - Total duration: ~3 months alongside full-time work - Starting baseline: 43% on the first TD practice exam My prep strategy: Watched ~90% of Maarek's SAP-C02 course - dense, well-structured, great refresher with new material Used Adrian Cantrill's SAP-C02 course for more complex topics and deep dives Generated text files with both course syllabuses and uploaded them to a Claude project - it would suggest exactly which video to watch for each gap I had, by name Completed all TD sets in study mode, reading every explanation Did the official AWS Skill Builder mock exam - highly recommended, best sample of the real exam feel Did 1 Maarek's mock exam Did one full TD exam in timed mode to practice exam pressure For complex topics drew diagrams by hand on paper - DX connectivity, AD and user management, etc. After each TD test, saved the full question-and-answer page as md file and added it to my Claude knowledge base for follow-up consultations After each full test, spent the next few days working through failed questions and re-doing them For unclear or complex questions, pasted the entire question into Claude for clearer explanations and heuristics Generated around 50 paper flashcards covering important facts and decision rules, reviewed them periodically Kept written by me + Claude generated notes in Obsidian AI coaching with Claude I used Claude as a persistent study partner throughout the 3 months: After each mock exam, pasted wrong answers into Claude for a breakdown Claude tracked patterns across sessions and flagged recurring weak areas proactively Together we built a heuristic library - short decision rules like: "When the question says 'least operational overhead', always prefer the managed or serverless option" "Global Accelerator = static IP + lowest latency together. Not Route 53." "LDAP + no SAML = identity broker in the middle, always" Flashcards were generated for each weak topic and later printed out Claude pointed me to specific course videos by name, so I never wasted time hunting for the right material For the last week before exam I even vibe coded a simple web app with all failed questions from all attempts and was reviewing that. The app just gave me a nice UI and navigation between questions, also test mode so I could easily re-test these questions. Progression numbers https://preview.redd.it/xy87hgltve6h1.png?width=1390&format=png&auto=webp&s=762acd7b869437d35eba32e39982b8655b70b053 The progression was not linear. I jumped from 42% to 64%, then regressed to 52% - discouraging, but it forced me to close gaps properly. Same story with AWS Skill Builder: failed at 635, then passed at 868. My theory: I had been grinding TD too long and started memorizing instead of learning. Switching mock providers exposed that issue. Rotate your sources - your brain needs to reason, not recall. Huge thanks to both Cantrill and Maarek for the work they do - their materials are gold and genuinely appreciated, you're legends! Happy to answer questions. Good luck to everyone preparing! submitted by /u/L1MB0_ [link] [comments]

I passed the AWS Solutions Architect - Associate certification exam with a score of 845! What's funny is that when I finished the exam, I was convinced I had failed. I flagged every question I wasn't confident about and ended up with 24 flagged questions by the time I submitted. My background I'm a software engineer with 8 years of experience in web development, but surprisingly little cloud experience. The company I've worked for over the last 5 years uses AWS extensively, but somehow I managed to avoid almost all infrastructure-related work until about 3 months ago, when I decided to start preparing for this certification. My preparation I studied for about 3 months using: Stephane Maarek's course on Udemy Jon Bonso's practice exams on Udemy AWS whitepapers, particularly around Disaster Recovery and the Well-Architected Framework The YouTube session: "AWS re:Invent 2024 - Backup and Disaster Recovery Strategies for Increased Resilience (COP319)" Tutorial Dojo's cheat sheets Practice exam scores Round 1 (Exam Mode) Exam 1: 70% Exam 2: 72% Exam 3: 72% Exam 4: 72% (at this point, I was getting discouraged because I felt like I wasn't making any progress) Exam 5: 63% (this exam was brutal for my morale; I briefly considered giving up) Exam 6: 80% Round 2 (Practice Mode, same exams) Exam 1: 83% Exam 2: 92% My experience with the exam I took the exam in-person at a testing facility. I felt the actual exam was more difficult than the practice exams I took, even though I ended up scoring higher than my average score on the practice exams. I was tested on services I wasn't familiar with, such as AWS X-Ray. One thing that caught me off guard was the presence of questions that required selecting three answers. The practice exams I took included "Select Two" questions, but I don't recall seeing any "Select Three" questions. Final Thoughts A big thank you to everyone who contributes to this subreddit. Reading other people's experiences helped me stay motivated when I was struggling. Good luck to everyone currently preparing for a certification! submitted by /u/BrilliantMonument [link] [comments]

New grad in Japan. I recently passed AWS SAA and am interested in cloud careers. However, my company assigned me to a Java + PostgreSQL project focused on authentication and security rather than an AWS-focused role. For experienced engineers: Does backend security/authentication experience transfer well to future cloud/AWS roles? 1.Is Java backend development still a good long-term career path in 2026? 2.Would you stay in this role for 1-2 years before moving toward cloud engineering? 3.I’d appreciate any advice from people who started in backend development and later moved into AWS/cloud. submitted by /u/OtherwiseIce7590 [link] [comments]

https://preview.redd.it/3zju9bs5tb6h1.png?width=779&format=png&auto=webp&s=3ac86492a8843564b664af2b9fe882c7caca5d09 I did the mareek udemy course, then TD exams. As I got >80% on all TD exams the first time, and ~95% second time I did each, I felt ready. Of the questions, 20 I've already seen in TD. But the rest were hard or about services I was not prepared, like many about AWS IAM Roles Anywhere. I've had to guess on some questions. submitted by /u/No_Independence_840 [link] [comments]

You can now create Amazon FSx for OpenZFS file systems with the Intelligent-Tiering storage class in 8 additional AWS Regions across the US, Europe, Asia Pacific, and South America. FSx Intelligent-Tiering is built for general-purpose file workloads such as file shares, archives, media libraries, and migrations from on-premises HDD storage. It automatically moves your data across three storage tiers (Frequent Access, Infrequent Access, and Archive) based on access patterns, and an optional SSD read cache keeps your active data fast. You get high performance for active workloads and low-cost storage for everything else, paying only for what you store with no capacity to manage. With FSx Intelligent-Tiering, you can save up to 85% compared to the FSx SSD storage class and up to 20% compared to on-premises HDD-based NAS. With this expansion, the FSx Intelligent-Tiering storage class is now available for FSx for OpenZFS file systems in the following additional AWS Regions: US West (N. California), Europe (London, Stockholm, Spain, Zurich), Asia Pacific (Hyderabad, Seoul), and South America (São Paulo). To learn more, visit the FSx Intelligent-Tiering page and the Amazon FSx for OpenZFS product page, and see the FSx for OpenZFS Region Table for complete regional availability information.

Amazon SageMaker Unified Studio Notebooks now support Amazon EMR Serverless with Apache Spark Connect, giving data engineers and analysts more flexibility in choosing their Spark runtime for interactive analytics and data engineering workloads. In addition to Amazon Athena Spark, users can now leverage Amazon EMR Serverless as their Spark runtime, selecting the optimal engine based on their requirements. With this launch, you can run PySpark and Spark SQL on an EMR Serverless Spark Application in Notebook cells. Users can select their Spark runtime from the Notebook side panel, and the selected runtime applies to both Python and SQL cells. Additionally, users can leverage SageMaker Data Agent, the built-in AI assistant, to generate code and execution plans from natural language prompts, accelerating Spark development workflows with EMR Serverless. Organizations can leverage pre-initialized capacity to improve session start times, while benefiting from unified Spark UI monitoring across all supported engines for consistent visibility into job execution and performance. Additionally, EMR Serverless provides VPC connectivity support for workloads requiring network isolation. This feature is available in all AWS Regions where Amazon SageMaker Unified Studio is available, supporting both SageMaker Unified Studio notebooks and JupyterLab IDE environments. To get started, see Amazon SageMaker Unified Studio User Guide.

You can now create Amazon S3 Access Grants in the AWS European Sovereign Cloud (Germany) Region. Amazon S3 Access Grants map identities in directories such as Microsoft Entra ID, or AWS Identity and Access Management (IAM) principals, to datasets in S3. This helps you manage data permissions at scale by automatically granting S3 access to end users based on their corporate identity. Visit the AWS Region Table for complete regional availability information. To learn more about Amazon S3 Access Grants, visit our product page.

I passed the AWS Solutions Architect Associate exam in a little over two months, and I wanted to share what worked for me in case it helps anyone else studying right now. I started with a full course first because I needed structure. I personally used Cloud Academy because a friend recommended it. It was around $50/month and gave me a decent foundation with hands-on labs, quizzes, and practice questions. That being said, I didn’t love it. If I had to study for the exam again, I would probably use Adrian Cantrill’s Solutions Architect course instead. From what I’ve seen, his course goes deeper and seems better if you actually want to understand the concepts long-term, not just memorize answers. After finishing the course, I went through the practice exams inside Cloud Academy. Anytime I didn’t understand something, I used ChatGPT to break it down until the concept actually made sense. This helped a lot with services that sounded similar, like SQS vs SNS vs EventBridge, NAT Gateway vs Internet Gateway, VPC endpoints, storage classes, and database options. After that, I bought the Tutorial Dojo practice exams. That was probably the most useful part of my prep. First, I did the exams in review mode so I could learn from the explanations. Then I started doing them timed, like the real exam. I also tracked every minute I studied using the Forest app. Total study time: 131 hours and 19 minutes. Overall, it took me a little over two months to pass. My biggest advice: Pick one solid course and stick with it. Don’t course-hop. Do a lot of practice questions, but don’t just memorize the answers. Read the explanations and understand why the wrong answers are wrong. Book the exam early so you have a real deadline. That helped me stay consistent. I also made a short video walking through how I passed and what I would do differently, but I figured https://www.instagram.com/reel/DZXzwyeOUDe/?igsh=MTVsa3Jlc2o2ZXY2ZA== I’d share the written breakdown here too since Reddit helped me a lot while I was studying. Hope this helps someone currently preparing for the exam. https://preview.redd.it/kefxcxi1ha6h1.jpg?width=1320&format=pjpg&auto=webp&s=26cde26d6bf9599b2433ad7fb68c8c8a0479db9c submitted by /u/Shaztheman [link] [comments]

Today, AWS announces the preview of AWS FinOps Agent, a frontier agent for FinOps practitioners and engineering teams that answers cost questions, surfaces optimization opportunities, automatically investigates cost anomalies, and runs recurring FinOps workflows on a schedule you define. With the AWS FinOps Agent, you can ask questions about your AWS costs and generate cloud cost reports for finance and engineering teams. The agent surfaces rightsizing, idle resource, and Savings Plans recommendations from AWS Cost Optimization Hub and AWS Compute Optimizer, and can open Jira tickets on your behalf. When a cost anomaly is detected, FinOps Agent can automatically investigate the root cause and can post the findings to a Slack channel, so engineering teams are notified without manual triage. AWS FinOps Agent (preview) is available in the US East (N. Virginia) Region and includes cost and usage data covering all AWS Regions, except AWS GovCloud (US) Regions and AWS China (Beijing and Ningxia) Regions. AWS FinOps Agent is offered at no additional charge during the preview. Learn more about AWS FinOps Agent in the User Guide, product details page, and the blog. Get started by visiting the AWS FinOps Agent page in the AWS Management Console.

AWS is announcing the general availability of metal-48xl and metal-96xl sizes for Amazon Elastic Compute Cloud (Amazon EC2) M8in, M8ib, M8idn, M8idb, R8in, R8ib, R8idn, and R8idb instances. These instances are powered by custom sixth generation Intel Xeon Scalable processors, available only on AWS and feature the latest sixth generation AWS Nitro cards. These instances deliver up to 43% better compute performance per vCPU compared to previous generation M6in, M6idn, R6in, and R6idn instances. M8in, M8idn, R8in, R8idn instances deliver 600 Gbps network bandwidth, the highest network bandwidth among enhanced networking EC2 instances. M8in and R8in instances are ideal for workloads such as real-time big data analytics, distributed web scale in-memory caches, caching fleets for AI/ML clusters, and Telco applications such as 5G User Plane Function (UPF). M8idn and R8idn instances are ideal for network-intensive general purpose workloads requiring local storage, such as distributed compute, data analytics, and high-performance file systems. M8ib, M8idb, R8ib, R8idb instances deliver up to 300Gbps EBS bandwidth, the highest among non-accelerated compute EC2 instances. M8ib and R8ib instances are best suited for workloads that benefit from high block storage performance, such as high-performance file systems and NoSQL databases. M8idb and R8idb instances are ideal for storage-intensive general purpose workloads such as large commercial databases, data lakes, and NoSQL databases that benefit from both high EBS throughput and low-latency local NVMe storage. M8in, M8ib, M8idn, M8idb, R8in, R8ib, R8idn, and R8idb instances support Elastic Fabric Adapter (EFA) networking on 48xlarge, 96xlarge, metal-48xl, and metal-96xl sizes. EFA networking enables lower latency and improved cluster performance for workloads deployed on tightly coupled clusters. The new metal-48xl and metal-96xl sizes are available in the AWS US East (N. Virginia) region. To get started, see AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs.

Claude Fable 5 is generally available on AWS and makes Mythos-level capabilities available to all customers, with strong safeguards designed to make it safe for broader use. Fable 5 is state-of-the-art on nearly all tested benchmarks and delivers a step-change in autonomous knowledge work and coding for developers and enterprises building production AI applications. Claude Mythos 5, the same model without those safety classifiers, is available to a small group of customers who currently have access to Claude Mythos Preview. Claude Fable 5 can run for extended periods on complex knowledge work and coding tasks without intervention, representing a fundamental shift in the types of problems customers can solve with AI. It is built for professional tasks in finance, legal, marketing, sales, data, and engineering — proactively self-updating skills based on learnings, developing its own evaluation harnesses, and verifying its work before delivery.  Customers have two ways to access Claude Fable 5: Amazon Bedrock and Claude Platform on AWS. Amazon Bedrock keeps your data within AWS infrastructure and provides access to Claude Fable 5 through a unified service with AWS-managed features like Guardrails, Knowledge Bases, and regional data residency. To learn more, see Amazon Bedrock documentation and regional availability.  Claude Platform on AWS, operated by Anthropic, gives you direct access to Anthropic's native Claude platform experience with unified AWS billing and authentication. To get started, see the Claude Platform on AWS documentation.

AWS Backup support for Amazon Elastic Kubernetes Service (EKS) is now available in the AWS European Sovereign Cloud (Germany) Region. This expansion brings fully-managed, policy-based data protection and recovery to your Amazon EKS clusters in this newly supported Region — including automated scheduling, retention management, immutable vaults, and cross-Region and cross-account copies. You can use AWS Backup for Amazon EKS to protect entire EKS clusters, specific namespaces, or individual persistent volumes using a centralized, agent-free solution that replaces custom scripts or third-party tools. Use AWS Backup to protect your clusters for disaster recovery, compliance requirements, or before EKS cluster upgrades. To get started, visit the AWS Backup console, refer to the AWS Backup documentation, or read the AWS News Blog.

submitted by /u/poojashakya_147 [link] [comments]

Amazon EMR Serverless now supports interactive sessions with Spark Connect, enabling you to develop and run Apache Spark applications from managed notebooks in Amazon SageMaker Unified Studio, as well as your favorite notebook environments and IDEs such as Jupyter and Visual Studio Code. You can also monitor and debug active and completed sessions in the EMR console, and get granular cost and usage visibility for individual sessions.    An interactive session provides a persistent Spark context that seamlessly spans across cells and scripts, enabling you to blend local Python code execution with remote Spark operations within a unified environment. This is enabled by Spark Connect's client-server architecture, which decouples your application client from the Spark driver and allows you to maintain your preferred development environment and tooling while Spark infrastructure runs independently on EMR Serverless. This architecture unlocks workflows including ad hoc data exploration, iterative step-by-step debugging, and incremental PySpark job development before deploying to production.  For observability, you get real-time session monitoring via the Spark UI, history tracking through the Spark History Server, and session management from the EMR console or API/CLI/SDK.   Spark Connect on Amazon EMR Serverless is available with EMR release 7.13 in all AWS Regions where Amazon EMR Serverless is available. The SageMaker Unified Studio experience is available in supported regions. To get started, visit the EMR Serverless Interactive Sessions User Guide or the Amazon SageMaker Unified Studio Getting Started guide.

AWS Cost Explorer now supports 'Analyze with Amazon Q', a new capability that delivers comprehensive cost explanations for any report you configure in Cost Explorer. With a single button click you now can receive detailed analysis from Amazon Q Developer covering your cost trends, top cost drivers, and anomalies. All analysis uses your exact filters and time-period and provides guidance to discover optimization opportunities through follow-up questions. Previously, cost analysis required manual investigation across multiple filters and data points. With 'Analyze with Amazon Q', you simply configure your Cost Explorer view and click a single button. Amazon Q analyzes your current context and delivers explanations directly in its chat panel, adapting to what you're viewing: historical explanations for past dates, forecast explanations for future dates, or both for mixed periods. You can then ask follow-up questions to explore any insights related to your cost data in greater detail as Amazon Q maintains full conversation context throughout. 'Analyze with Amazon Q' is available in all commercial AWS Regions at no additional charge. To get started, visit the AWS Cost Explorer console, or view the user guide.

Planning to study for the Solutions Architect Associate over the next ~3 months. The catch is it's not my only thing, my main focus is DSA/LeetCode for interviews, and I also work part-time about 3-4h a day (not mentally heavy). My rough plan is DSA in the mornings when I'm fresh and AWS at a calmer ~1–1.5h/day pace. For anyone who's juggled SAA alongside other serious study or work: is this realistic, or am I underestimating it? Any tips on fitting SAA prep around a bigger priority would be appreciated. submitted by /u/Fun-Contribution4477 [link] [comments]

Successfully passed today with a 823. Resources: **Stephane Marek Udemy Course** This was an excellent course, very well done. **Tutorials Dojo Practice Exams + Cheatsheets** Completed all 4 practice exams in review mode with scores averaging 65-69%. Completed 1 random test and got 84%. If your passing dojos exams, you will be fine for the exam submitted by /u/ThatSecGuy [link] [comments]

Lately I’ve seen a lot of people proudly flexing the AWS Golden Jacket as if it’s the cloud equivalent of being knighted. Genuine question: what’s the actual value of pursuing it? How has it helped your career, compensation, credibility, or day-to-day effectiveness as an engineer? Did it open doors that wouldn’t have opened otherwise, or is it mostly a personal achievement and learning milestone? Maybe I’m missing something, but when I see a long list of certifications, my first reaction isn’t “expert.” It’s usually, “Interesting… are we looking at a specialist, or a highly certified jack-of-all-trades?” Not trying to start a certification war—I’m genuinely curious how Golden Jacket holders and hiring managers view its real-world impact versus hands-on experience building and operating systems at scale. submitted by /u/green3415 [link] [comments]

AWS Compute Optimizer now identifies idle resources for Amazon DynamoDB provisioned tables, Amazon ElastiCache (Redis and Valkey), Amazon MemoryDB, Amazon DocumentDB (provisioned and serverless), Amazon WorkSpaces, and Amazon SageMaker endpoints. This expansion enables you to detect unused resources across more of your AWS environment and identify potential cost savings. Compute Optimizer analyzes utilization metrics to determine whether a resource is idle. Customers can set this lookback period based on the nature of their workloads. For each resource type, Compute Optimizer evaluates service-specific signals such as consumed capacity, cache hits, active connections, and CPU utilization. When Compute Optimizer identifies potential idle resources, it surfaces these recommendations, along with detailed utilization metrics and estimated savings in the console, enabling you to evaluate recommendations before acting. You can also view idle resource recommendations across all AWS accounts in your organization through the Cost Optimization Hub, with de-duplicated estimated savings with other recommendations on the same resources. For more information about the AWS Regions where Compute Optimizer is available, see the AWS Region table. For more information about AWS Compute Optimizer, visit our product page and documentation. You can start using AWS Compute Optimizer through the AWS Management Console, AWS CLI, and AWS SDK.

Effective today, Amazon MSK Express Brokers support automatic topic creation with Kafka Streams. Customers can now deploy their Kafka Streams applications on Express Brokers without needing to manually pre-create or manage topics for stateful operations. MSK Express Brokers are designed to deliver up to three times more throughput per broker, scale up to 20 times faster, and reduce recovery time by 90 percent. Kafka Streams uses topics to store state and repartition data for stateful operations. Previously, customers running Kafka Streams with Express Brokers had to manually name and pre-create these topics before deploying their application. With this launch, these topics are created automatically when the application starts, simplifying deployment and reducing operational setup for Kafka Streams applications on Express Brokers. This capability is available today in all AWS regions where MSK Express Brokers are available. No additional configuration or setup is required to get started. To learn more, see Amazon MSK Developer Guide.

Amazon DocumentDB (with MongoDB compatibility) now supports engine minor versions, starting with 5.0.1. This release delivers enhanced aggregation capabilities with new operators ($rand, $pow, $dateToParts, $dateFromParts), the active connections metric to monitor instances, and granular command-level performance metrics in CloudWatch (find, insert, findAndModify, update, etc.). For a full list of what's included, see release notes. Minor versions provide new features and bug fixes within the same major version, giving you more control over when and how you upgrade your clusters. We recommend upgrading to the latest minor version to benefit from these performance enhancements, bug fixes, and new capabilities. You can specify minor version 5.0.1 when creating a new cluster, or manually upgrade an existing 5.0.0 cluster to 5.0.1 using the AWS Management Console or AWS CLI (via the modify-db-cluster command with --engine-version 5.0.1). Once you upgrade to a newer minor version, you cannot downgrade back to a previous minor version. Upgrading from 5.0.0 (LTS) to 5.0.1 gives you access to the latest features and fixes, but you will no longer be on the LTS track. If minimizing upgrades is your priority, you should remain on LTS. For more information, see Using a long-term support (LTS) release. Amazon DocumentDB engine minor version 5.0.1 is available in all AWS Regions where Amazon DocumentDB 5.0 is available. Learn more about minor version upgrades and version support dates in the Amazon DocumentDB Developer Guide. Create or update a fully managed Amazon DocumentDB cluster in the Amazon DocumentDB Management Console.

Amazon CloudWatch Logs Insights query language now supports 23 new commands and functions that give you new ways to query, parse, transform, and analyze your logs. Customers analyzing logs in CloudWatch Logs Insights often need to do conditional processing, string conversions, process IP addresses, parse different file formats, and execute complex stats commands. With this launch, CloudWatch Logs Insights provides new hash functions (md5, sha256), string functions (strcontains supporting case-insensitive search, split), conditional logic (if statement), and conversion functions (toNumber, toInt, toLong, toDouble). It also adds IP functions (ipv4ToNumber, isPrivateIP, isPublicIP, isReservedIP), analytics functions (rate, count_over_time, sum_over_time, offset, histogram), and parse functions (parse CSV, parse XML, parse multi, values, addtotals). Additionally, queries now support “limit any N” to fetch the first N results, and can use up to 10 stats commands. These commands and functions are available today in all commercial AWS Regions. To learn more, see the Amazon CloudWatch Logs documentation.

Today, AWS announces target coverage analysis in Savings Plans Purchase Analyzer, a capability in AWS Billing and Cost Management that helps you plan your Savings Plans purchases based on your coverage target. Savings Plans Purchase Analyzer helps you evaluate different purchase scenarios by estimating the potential impact of Savings Plans purchases on cost, coverage, utilization, and savings. With target coverage analysis, you can set a specific percentage of On-Demand spend to be covered by Savings Plans. Savings Plans Purchase Analyzer uses your historical usage to recommend a new purchase amount to help you reach that target. You can further customize your analysis using parameters such as custom lookback period or excluding expiring Savings Plans, and compare cost, coverage, utilization, and savings across different coverage targets. You can view your recommendations through interactive charts or access your target coverage analysis via the Purchase Analyzer API. Target coverage analysis is available in all AWS Regions where Savings Plans Purchase Analyzer is available. To learn more, visit the AWS Savings Plans page and user guide.

Like the title says, I come from a Microsoft Azure shop and I’m decently versed in that area. I have an Azure Administrator certification which is the same as the administrator cert for AWS I believe. I set up a free account to take a look at an AWS environment and aside from a few name changes AWS seems a bit easier to understand. That said, with no actual experience in AWS would you think it possible I can skip the line a bit and jump straight to a solutions architect certification? It seems the most in demand, and it also sounds like Udemy and TD would be the two main resources I need along with some real world practice. If anyone has any advice I am open to it, or if anyone knows how hard/easy the exam is or even what to expect. submitted by /u/Electronic-Clerk6735 [link] [comments]

Amazon RDS for PostgreSQL 19 Beta 1 is now available in the Amazon RDS Database Preview Environment, allowing you to evaluate the pre-release of PostgreSQL 19 on Amazon RDS for PostgreSQL. You can deploy PostgreSQL 19 Beta 1 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database. PostgreSQL 19 adds native graph query support via SQL Property Graph Queries (SQL/PGQ), so you can express complex relationship traversals directly in standard SQL instead of building separate application logic or syncing data across two databases. It also introduces support for concurrent table repacking that rebuilds tables and reclaims unused storage, so production databases stay accessible during routine table maintenance. Logical replication now synchronizes sequence values to the replica automatically, eliminating manual sequence reconciliation after major version upgrade cutover. Logical replication can also be enabled dynamically without a server restart, reducing planned downtime. Please refer to PostgreSQL community announcement for more details. Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment. You can use the PostgreSQL dump and load functionality to import or export your databases from the preview environment. Amazon RDS Database Preview Environment database instances are priced as per the pricing in the US East (Ohio) Region.

AWS Lambda Managed Instances (LMI) is now available in all commercial AWS Regions, except Israel (Tel Aviv), Middle East (Bahrain), Middle East (UAE), and Asia Pacific (Auckland).   LMI lets you run Lambda functions on managed Amazon EC2 instances, giving you access to specialized compute configurations and EC2 pricing advantages while maintaining Lambda's operational simplicity. LMI fully manages instance lifecycle, OS and runtime patching, routing, load balancing, and auto-scaling, so you can focus on writing code. You can process parallel requests within each execution environment, maximizing resource utilization and improving price-performance. You can further improve costs by leveraging EC2 pricing models including Compute Savings Plans and Reserved Instances. LMI is ideal for customers requiring specialized hardware configurations, as well as those with steady-state or predictable workloads seeking to optimize costs. You can continue building functions with familiar development workflows, including the Console and your preferred IDEs. To get started, create a capacity provider that defines your compute preferences, including VPC configuration, optional instance requirements, and scaling policies. Then, attach your Lambda functions to the capacity provider via the AWS Lambda Console, APIs, or Infrastructure as Code tooling. LMI integrates seamlessly with all Lambda event sources and tools like Amazon CloudWatch, AWS X-Ray, and AWS Config. To learn more, visit AWS Lambda pricing, AWS Lambda Managed Instances documentation, and blog. 

AWS Application Migration Service (MGN) is now available as AWS Transform MGN. This name change reflects MGN's role as the proven replication engine powering AWS Transform, the agentic migration service. You can choose between two rehosting experiences. Use the AWS Transform MGN console for direct control over replication and cutover. Or use the AWS Transform agentic workflow, where an agent handles discovery, wave planning, landing zone setup, network creation, and rehosting or containerization on your behalf, accelerating your path to AWS. AWS Transform MGN retains all of its existing compliance certifications, including FedRAMP High, HIPAA, PCI DSS, ISO, and SOC 1, 2, and 3, so you can migrate with confidence. It is available in all commercial regions and both GovCloud (US) Regions. Visit the AWS Transform MGN product page and AWS Transform MGN documentation for more information on how to rehost applications to AWS.

Amazon Aurora DSQL introduces support for the PostgreSQL JSONB data type with optional compression. You can now use code and tools that depend on PostgreSQL's JSONB type with Aurora DSQL, making it easier to store semi-structured data alongside relational data. You can use the JSONB data type when creating or modifying tables to store semi-structured data such as system configuration metadata, API parameters, and event logs. With PostgreSQL compression enabled by default, larger JSONB payloads are stored more efficiently, helping reduce storage costs. Get started with Aurora DSQL for free with the AWS Free Tier. For information about Regional availability, see the AWS Region table. You can learn more about Aurora DSQL data types, including JSONB, here.

AWS Cost Anomaly Detection now includes AI-powered cost investigation, which uses Amazon Q to analyze the root cause of detected cost anomalies. Investigating a cost change typically requires correlating cost data with AWS CloudTrail events and resource activity, which can take hours. Cost investigation delivers a plain-language explanation in minutes, helping FinOps practitioners and engineering teams move from alert to action faster. When you investigate an anomaly, Amazon Q determines whether the cost change is usage-driven or rate-driven, identifies the contributing services, accounts, and regions, and for usage-driven changes, correlates with AWS CloudTrail to attribute the change to specific API calls and IAM principals. For organizations with a CloudTrail organization trail, the investigation works across all member accounts automatically. You can continue the conversation with follow-up questions to explore patterns or drill into specific resources.  AI-powered cost investigation is available today in all commercial AWS Regions at no additional charge. Cross-account investigations that use an organization-wide CloudTrail trail delivered to Amazon CloudWatch Logs might incur standard CloudWatch Logs Insights charges based on data scanned. To get started, navigate to AWS Cost Anomaly Detection in the AWS Billing and Cost Management console and choose Investigate with Amazon Q on any detected anomaly. To learn more, see Investigating anomaly root causes with Amazon Q in the AWS Billing and Cost Management User Guide. 

Prepping for the AWS Certified Generative AI Developer Professional (AIP-C01) exam and finding a lot of noise in the study materials. Many third-party practice tests seem to test generic data science concepts rather than actual AWS implementation. For those who passed recently: Which practice tests or question banks truly mirror the multi-sentence scenario questions on the real exam? I’m looking for high-quality practice specifically targeting Bedrock orchestration, RAG architectures, and Guardrails/PII masking. What resources should I actively avoid? Drop your recent exam tips below! submitted by /u/CommunicationCute579 [link] [comments]

Amazon Connect Customer now provides AI agent traces for self-service voice interactions, enabling you to understand how AI agents reason, act, and respond during each customer conversation. With this launch, you have full visibility into how the AI agent handled an interaction, so you can confirm what worked, diagnose issues, validate behavior, and deploy agentic experiences with confidence. For example, if your AI agent fails to resolve a customer request, you can access the step-by-step trace directly in the Connect web UI alongside the full transcript, and see whether it reasoned incorrectly, called a tool with bad parameters, or timed out waiting for a response. This feature is available in all AWS Regions where Amazon Connect Customer AI Agents are supported. For more information, see the Amazon Connect Customer Administrator Guide. To learn more about Amazon Connect Customer, an agentic AI solution that helps enterprises deliver exceptional customer experiences, visit the Amazon Connect Customer website.

Amazon Redshift announces a new billing model for manual snapshots on Amazon Redshift Serverless and Amazon Redshift RG instances. With this enhancement, Amazon Redshift now meters manual snapshot storage based on the unique data blocks stored across your snapshots rather than the total size of each individual snapshot. This results in lower manual snapshot costs for customers who maintain multiple snapshots. Customers who maintain multiple manual snapshots for disaster recovery, testing, or long-term retention will see reduced storage costs. With this new billing model, you can take more frequent manual snapshots to achieve a better recovery point objective (RPO) without proportional cost increases, enabling more robust disaster recovery strategies. The new billing model automatically applies to both existing and new manual snapshots. The new manual snapshot billing model is available in all AWS commercial and AWS GovCloud (US) Regions where Amazon Redshift Serverless and Amazon Redshift RG instances are available. To learn more about Amazon Redshift snapshots, please visit our documentation or the blog.

While I have been reading motivational post of people who passed their CCP exams I was happy to try after been refused from writing the exam two weeks ago because I arrived at the Pearson vue exam center with just one ID. Rebooked and Passed. Funny enough I got 745/1000😂😂😂 It would have been crazy if I didn’t pass the cut off mark. But I earned this. As I am transitioning from marketing to tech😬😩 I am Kinda thinking about what’s next … anyone here transitioned and found their bearing??? submitted by /u/Maybs_ [link] [comments]