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Dynatrace supports SnapStart for Lambda as an AWS launch partner

Dynatrace

Dynatrace is proud to be an AWS launch partner in support of Amazon Lambda SnapStart. For AWS Lambda, the largest contributor to startup latency is the time spent initializing an execution environment, which includes loading function code and initializing dependencies. What is Lambda? What is Lambda SnapStart?

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Hashnode Creates Scalable Feed Architecture on AWS with Step Functions, EventBridge and Redis

InfoQ

Hashnode created a scalable event-driven architecture (EDA) for composing feed data for thousands of users. The company used serverless services on AWS, including Lambda, Step Functions, EventBridge, and Redis Cache. The solution leverages Step Functions' distributed maps feature that enables high-concurrency processing.

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AWS serverless services: Exploring your options

Dynatrace

Scalability. Finally, there’s scalability. Lambda functions can be written in the language of your choice, and the service also supports container tools. Amazon EventBridge: EventBridge to bridges the data gap between your applications and other services, such as Lambda or specific SaaS apps. Data Store.

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Cloudburst: stateful functions-as-a-service

The Morning Paper

Last week we looked at a function shipping solution to the problem; Cloudburst uses the more common data shipping to bring data to caches next to function runtimes (though you could also make a case that the scheduling algorithm placing function execution in locations where the data is cached a flavour of function-shipping too).

Lambda 98
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Radically speed up your code by fixing slow or frequent garbage collection

Dynatrace

However, garbage collection is one of the main sources of performance and scalability issues in any modern Java application. Depending on your application, you may be faced with one of these challenges: Slow garbage collection : This can impact your CPU massively and can also be the main reason for scalability issues.

Speed 165
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Fast key-value stores: an idea whose time has come and gone

The Morning Paper

Generally to cache data (including non-persistent data that never sees a backing store), to share non-persistent data across application services (e.g. ” Even re-reading that today, the letter of the law there is surprisingly strict to me: you can use the local memory space or filesystem as a brief single transaction cache, but no more.

Cache 79
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Choosing a cloud DBMS: architectures and tradeoffs

The Morning Paper

Which I’m quite happy to see as my most recent data pipeline is based around Lambda, S3, and Athena, and it’s been working great for my use case. For query executors that can be frequently started and stopped the authors explore performance with cold and warm caches (where applicable), and also the horizontal and vertical scaling performance.