Denis Fedotenko’s Post

How did we introduce #LowerPrices? Earlier this week, we launched Amazon #ElastiCache for #Valkey and Amazon #MemoryDB for #Valkey, introducing significant lower prices. If you missed this launch see here: https://lnkd.in/g9xwBqip. Some people asked me how we were able to do that. Here is the short answer. To recap, ElastiCache #Serverless for Valkey is priced 33% lower than other supported engines and has 90% lower minimum data storage compared to other ElastiCache Serverless engines. ElastiCache node-based (self-designed) for Valkey is priced 20% lower than other supported engines. MemoryDB for Valkey is priced 30% lower than other engines, with an 80% lower price on data written after a new 10TB free tier. Here is how. We have heard from customers that #cost optimization is important to them. This is why we have launched a number of ways to improve price/performance: from reserved nodes, which provide a discount of up to 55%, to data tiering, which provides up to 60% cost savings, to multiple innovations with Enhanced I/O Multiplexing, which can boost performance to over 1M RPS per node, allowing you to run the same workload with fewer nodes. We have also contributed some of these performance innovations to open source (https://lnkd.in/g9scsepd). We continuously look for ways to improve #efficiency and #performance for customers. Just last week, we introduced size #flexibility for reserved nodes for all of our engines: https://lnkd.in/g3yJKc-S. At re:Invent 2023, we launched ElastiCache Serverless, providing an even easier way to get started with a cache with pay-per-use pricing model that helps customers avoid paying for overprovisioning. This year, we have focused on improving serverless hardware utilization and scaling efficiency. A lot of engineering innovation went into it, and we are excited to pass these efficiency gains to ElastiCache for Valkey customers. With MemoryDB, in the last couple of years, we have improved the efficiency of our Multi-AZ transaction log that powers MemoryDB, making it even more cost-effective to store writes across multiple availability zones in single-digit milliseconds. Similar to ElastiCache Serverless, we are passing these efficiency gains to our MemoryDB for Valkey customers. We are excited about the future Valkey and want customers to fully realize the benefits the engine has to offer! See how to get started with ElastiCache for Valkey here: https://lnkd.in/gvdszdfh See how to get started with MemoryDB for Valkey here: https://lnkd.in/guRi3aSD #aws #awscloud #lowercost #costoptimization #performance #efficiency

I am thrilled to announce that we have added support for Valkey 7.2 to Amazon ElastiCache and Amazon MemoryDB, our fully managed in-memory services! 🚀 With these launches, we introduced significant lower prices. See my other post about it here: https://lnkd.in/gY5477iu. Valkey is an open source high performance key-value datastore used for a variety of use cases such as caching, leaderboards, and session stores. It is designed as a drop-in open source replacement for Redis OSS and is developed by long standing Redis OSS contributors and maintainers. It is stewarded by the Linux Foundation and backed by 40+ companies. We have seen rapid adoption since the project inception in March 2024, with over 500K docker container pulls. We are now adding Valkey to our fully managed services, ElastiCache and MemoryDB. With this launch, customers can benefit from a fully managed experience built on Valkey's open-source technology, while taking advantage of the 13+ years of operational excellence, security, 99.99 availability SLA, and reliability that ElastiCache and MemoryDB provide. We believe open source is good for everyone, and we are actively contributing to Valkey. We have a long history of contributions to Redis OSS and now to Valkey, starting as early as 2015. Some of the recent contributions include fine grained access control over keys and commands, native hostname support for cluster configuration, and partitioned channels for scalable pub/sub that were released with Redis OSS version 7. We contributed Valkey GLIDE, an open source Valkey (and Redis OSS) compatible client. Valkey GLIDE is easily configurable and a reliable way to connect to Valkey and Redis OSS datastores. We also contributed to Valkey 8, including performance and efficiency improvements of up to 230% better throughput, up to 70% better latency, and up to 20% more memory efficiency. We will continue investing in Valkey and open source. See more details here: https://lnkd.in/g9xwBqip See how to get started with ElastiCache for Valkey here: https://lnkd.in/gvdszdfh   See how to get started with MemoryDB for Valkey here: https://lnkd.in/guRi3aSD More on Valkey: https://valkey.io/ and on GitHub: https://lnkd.in/gqrqXKrf Valkey GLIDE: https://lnkd.in/gf2HsHfs #aws #awscloud #opensource #valkey #elasticache #memorydb #inmemory #costoptimization #performance #glide

Who doesn’t love lower prices? I am thrilled to announce the GA of Amazon ElastiCache for Valkey and Amazon MemoryDB for Valkey! 🚀 With these launches, we introduced significant lower prices! Amazon ElastiCache for Valkey is priced 33% lower than other supported engines and has 90% lower minimum data storage compared to other ElastiCache Serverless engines. With these changes, you can create ElastiCache Serverless for Valkey cache in under a minute and get started at a low cost of $6/month. ElastiCache node-based (self-designed) is priced 20% lower than other supported engines. Amazon MemoryDB for Valkey is priced 30% lower than MemoryDB for Redis OSS. Additionally, customers who are using ElastiCache reserved nodes can easily switch from ElastiCache for Redis OSS to ElastiCache for Valkey, and retain their existing discounted reserved node rates across all node sizes within the same family. The same is true for MemoryDB reserved nodes. If you are an existing ElastiCache for Redis OSS customer or existing MemoryDB customer, you can just upgrade to ElastiCache for Valkey or MemoryDB for Valkey in a few clicks with no downtime to benefit from these prices! If you are still not using ElastiCache and MemoryDB see the links below on how to get started. Hundreds of thousands of customers use Amazon ElastiCache to boost their applications' performance, achieve higher scale, and optimize their cost. With ElastiCache for Valkey, customers can benefit from a fully managed experience built on open source technology while taking advantage of the 13+ years of operational excellence, security, 99.99 availability SLA, and reliability that ElastiCache provides. See how to get started here: https://lnkd.in/gvdszdfh Amazon MemoryDB for Valkey is an in-memory database service that delivers ultra-fast performance. MemoryDB is designed for durability and stores the data both in memory and in a Multi-AZ durable transactional log. This architecture enables you to achieve microsecond read latency, single-digit millisecond write latency, and high throughput, using Valkey’s popular open source APIs. See how to get started here: https://lnkd.in/guRi3aSD #aws #awscloud #opensource #valkey #elasticache #memorydb #inmemory #costoptimization #performance

Amazon Aurora Serverless can now scale down to 0 capacity units (ACUs), making it cost-effective when your application is idle. ✅ So, you can run MySQL or PostgreSQL databases in a truly serverless mind. You only pay for when your app is used. ❌ However, it is not ideal if your application cannot handle slow response times because there is a 15-second delay ⏳ when Aurora Serverless re-increases capacity from zero. 👉 https://lnkd.in/dz4q23FV

🚀 Boost Your Web Application’s Performance with Amazon ElastiCache! 🚀 Is your web app slowing down under the weight of heavy traffic? 🕒 Page load times matter more than ever for user experience and conversions. Here’s how Amazon ElastiCache can help you level up your application’s performance: 🔹 What is Amazon ElastiCache? Amazon ElastiCache is a fully managed, in-memory data store, supporting Redis and Memcached. It's designed to reduce latency and enhance app performance by caching frequently accessed data. 🔹 How ElastiCache Improves Performance: Reduce Database Load: Instead of hitting your primary database for every request, ElastiCache stores frequently used data in-memory, offering millisecond response times. 🔹 Increase Scalability: By caching data like session states, API responses, and user data, your application can handle more requests efficiently, even during traffic spikes. 🔹 Lower Latency: With ElastiCache, data can be retrieved quickly from the cache rather than from slower backend data stores. 🔹 Seamless Integration: ElastiCache integrates smoothly with applications deployed on AWS, making setup and scaling easy. 🔹 Real-World Use Cases: Session management: Cache user sessions in Redis for fast retrieval. Leaderboards: Use Redis Sorted Sets to keep real-time rankings. 🔹 API Caching: Cache expensive API calls for rapid responses. Implementing ElastiCache for your web app can drastically improve performance while keeping your backend infrastructure lightweight and cost-efficient. #AWS #WebDevelopment #CloudComputing #Caching #Redis #Memcached #ElastiCache #PerformanceOptimization #DevOps #Scalability

My 2nd project: 𝗗𝗲𝗰𝗼𝘂𝗽𝗹𝗶𝗻𝗴 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗶𝗻 Amazon Web Services (AWS)   Coming from a server world, where everything resides on a piece of hardware, I must confess that the term “serverless” sent shivers down my spine. What does that even mean? You create an app that it is not stored on a server? Where is that stored? So, basically, serverless means less maintenance, you focus on your app while AWS manages the servers for you. Isn’t that AWeSome?   𝗪𝗵𝗮𝘁’𝘀 𝘁𝗵𝗶𝘀 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗮𝗯𝗼𝘂𝘁? You can find more details here: https://lnkd.in/dT9nZahu   I designed a Serverless Order Processing tool to decouple the components of a cloud application, ensuring that all pillars of the AWS Well-Architected Framework are addressed. 🛠️   Here’s how it works: 𝗔𝗣𝗜 𝗚𝗮𝘁𝗲𝘄𝗮𝘆 receives order data via a POST request. This triggers a 𝗟𝗮𝗺𝗯𝗱𝗮 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻 which: Sends the order to a 𝗦𝗤𝗦 𝗙𝗜𝗙𝗢 𝗾𝘂𝗲𝘂𝗲. Publishes the SQS message to an email via an 𝗦𝗡𝗦 𝘁𝗼𝗽𝗶𝗰. Writes the order details in 𝗗𝘆𝗻𝗮𝗺𝗼𝗗𝗕.   💡 Years of creating hardware configs have taught me how to dig deep, search, and find the information I need.   𝗠𝘆 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗶𝘀 𝗽𝗿𝗼𝗷𝗲𝗰𝘁:   ✅ I took a deep dive into serverless architecture and learned how different AWS services work together. ✅ I discovered that Lambda doesn’t support SQS FIFO as a destination by default. So, I tackled this challenge by modifying the Lambda code. ✅ I found out that when you create an API Gateway from the Lambda console, the default method is set to ANY. I changed it to POST to improve security. ✅ I created a role and attached three resource-based policies to enhance our cloud environment's security. ✅ I enjoyed exploring how Lambda can handle multiple tasks - it's fascinating how much can be done with just one function.   🌟 I'm always on the lookout for new learning opportunities. If you have any tips or feedback, please share them!   Or, if you were an interviewer, what’s a great question you would ask about a serverless project? Let’s help each other out and build a strong community. 🤝   🛡️ Don’t forget to sanitize your screenshots to keep your private information secure. #CloudComputing #AWS #Serverless #CloudProject #Lambda #Netherlands

𝗧𝗵𝗲 𝗥𝗶𝘀𝗲 𝗼𝗳 𝗩𝗮𝗹𝗸𝗲𝘆: 𝗔 𝗡𝗲𝘄 𝗘𝗿𝗮 𝗶𝗻 𝗞𝗲𝘆-𝗩𝗮𝗹𝘂𝗲 𝗗𝗮𝘁𝗮𝘀𝘁𝗼𝗿𝗲𝘀 In March 2024, shortly after Redis Inc. announced that future versions of Redis would no longer be open-source, the Linux Foundation, along with Redis OSS developers and contributors, came together to launch the Valkey project. Valkey is an open-source, high-performance key-value, in-memory datastore, designed as a drop-in replacement for Redis OSS. Valkey’s Journey and Adoption: 🔖 𝗟𝗮𝘂𝗻𝗰𝗵 𝗼𝗳 𝗩𝗮𝗹𝗸𝗲𝘆: Officially launched in March 2024, Valkey quickly gained industry support. 🔖 𝗦𝘁𝗲𝘄𝗮𝗿𝗱𝘀𝗵𝗶𝗽 𝗯𝘆 𝘁𝗵𝗲 𝗟𝗶𝗻𝘂𝘅 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻: Later in March 2024, the Linux Foundation took stewardship of Valkey, ensuring its long-term viability and vendor neutrality. This move reassures the community that the open-source license remains intact and free from the influence of any single organization. 🔖 𝗣𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽𝘀 𝗮𝗻𝗱 𝗠𝗮𝗿𝗸𝗲𝘁 𝗣𝗼𝘀𝗶𝘁𝗶𝗼𝗻: By June 2024, Valkey had formed new partnerships with AWS, Google Cloud, Oracle, Ericsson, and Snap Inc., further solidifying its market position. 🔖 𝗥𝗮𝗽𝗶𝗱 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻: With over 500K container pulls, thousands of contributions, and support from over 40 companies, Valkey has seen rapid adoption in the last six months. The vibrant developer community continues to drive its improvements and innovations. 🔖 Google Cloud : Google announced Memorystore supports Valkey 8.0 on October 4th, offering unmatched performance and reliability as a fully managed service, building upon the launch of Memorystore for Valkey 7.2 in August 2024. 🔖 Amazon Web Services (AWS): Yesterday evening, Matt Garman, CEO of AWS, announced that Amazon ElastiCache and Amazon MemoryDB now support support for Valkey 7.2. This integration allows users to leverage Valkey as a drop-in replacement for Redis OSS, enhancing flexibility and performance. 🎲 𝗖𝗮𝗻 𝗩𝗮𝗹𝗸𝗲𝘆 𝗖𝗼𝗺𝗽𝗲𝘁𝗲 𝘄𝗶𝘁𝗵 𝗥𝗲𝗱𝗶𝘀?  Valkey's open-source nature, combined with its high performance and extensive feature set, positions it as a strong competitor to Redis. With the backing of major cloud platforms and a vibrant community, Valkey is well-equipped to meet the demands of modern applications and could very well rival Redis in the near future. Valkey GLIDE is an official client library for Valkey that supports all Valkey commands. It also supports Redis open source 6.2, 7.0, and 7.2. Valkey will also continue development on Redis 7.2.4 and will keep the project available for use, as announced by Linux Foundation on this March. 📌 For more details on the latest announcement, check out the AWS Blog: [AWS Blog] https://lnkd.in/gcdBwT6d 📌 Valkey on Github: https://lnkd.in/gVF5vikK #Valkey #OpenSource #CloudComputing #AWS #GoogleCloud #Redis #DataStorage #Innovation #LinuxFoundation #Valkey #GLIDE

🚀 New Amazon #DynamoDB and Amazon Keyspaces pricing reductions. 💲✂️ Price cuts are how AWS passes on the economic efficiencies gained from our scale and innovation back to our customers. Read the blog about the new pricing reductions here 👉 https://go.aws/3Ob3JJu Some key highlights: 📣 DynamoDB on-demand pricing is reduced by 50%. 📣 DynamoDB global tables on-demand replicated write pricing is reduced by 67%. 📣 DynamoDB global tables provisioned replicated write pricing is reduced by 33%. 📣 Keyspaces on-demand pricing is reduced by 56% for single-Region and 65% for multi-Region. 📣 Keyspaces provisioned pricing is reduced by up to 13% for single-Region and up to 20% for multi-Region. ...and there are additional pricing reductions. #NoSQL has never been so affordable!💥

Here's a nice article by Luc van Donkersgoed, where he describes how he improved the speed of his website, and prepared it to scale, by serving APIs through CloudFront, and redesigning them to benefit from caching when it makes sense. 👉 https://lnkd.in/e5KfgGuw AWS is making it easier for customers to serve dynamic content, such as APIs, using CloudFront. Few days ago, AWS Application Load Balancer launched an integration in the Console, allowing customers to easily serve content using CloudFront with an AWS WAF protection. I will talk about it more in the coming days. 👉 https://lnkd.in/ew4YRwaS Following me for similar news from AWS. #cloudfront #alb #performance #waf

How Uber Scales to 40 Million Reads Per Second with Integrated Redis Caching? In 2020, Uber introduced Docstore, their in-house, distributed database built atop MySQL, designed to handle vast amounts of data and millions of requests per second. Over time, it became the go-to for all Uber's business needs, thanks to its low latency, high performance, and scalability. 1. Challenges in Achieving Low Latency: Databases struggle with low-latency reads due to disk retrieval speed limits, and both vertical and horizontal scaling have their drawbacks, being costly and operationally complex. 2. Solution via Caching: To mitigate these challenges, Uber incorporated Redis for distributed caching, allowing for efficient reads directly from the cache. However, managing individual Redis clusters and cache invalidation logic across microservices proved challenging. 3. Introducing CacheFront: Uber developed CacheFront, an integrated caching solution, to reduce scaling needs, improve latencies, and centralize caching efforts, making caching transparent to service teams and decoupling it from Docstore's partitioning schema for better scalability and cost-efficiency. CacheFront's Architecture and Strategies: 1. Cached Reads: Utilizes a cache aside strategy, pulling data from Redis and backfilling the cache as necessary. 2. Cache Invalidation: Employs CDC (Change Data Capture) via Flux for timely cache updates, supplemented by TTL adjustments and dedicated APIs for stronger consistency needs. 3. Scalability and Resiliency: Features include compare cache for consistency checks, cache warming for failover readiness, sharding to handle large volumes of requests, and a circuit breaker to manage Redis node failures. 4. Impact: CacheFront significantly improved performance, reduced latencies by up to 75%, achieved 99.9% cache consistency, and supported over 40M requests per second, showcasing a scalable, cost-effective solution for Uber's caching needs. #TechInnovation #DataManagement #Scalability #PerformanceOptimization