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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. This significantly increases event latency.

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Bending pause times to your will with Generational ZGC

The Netflix TechBlog

Reduced tail latencies In both our GRPC and DGS Framework services, GC pauses are a significant source of tail latencies. In fact, we’ve found for our services and architecture that there is no such trade off. No explicit tuning has been required to achieve these results.

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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 1 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Hundreds of millions of customers tune into Netflix every day, expecting an uninterrupted and immersive streaming experience. Logging is selective to cases where the old and new responses do not match.

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Optimizing your Kubernetes clusters without breaking the bank

Dynatrace

However, setting the right parameters for Kubernetes clusters to ensure application availability, performance, and resilience while avoiding overspending isn’t a walk in the park. Tuning thousands of parameters has become an impossible task to achieve via a manual and time-consuming approach. The Akamas approach. lower than 2%.).

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Comparing PostgreSQL DigitalOcean Performance & Pricing – ScaleGrid vs. DigitalOcean Managed Databases

Scalegrid

Compare Latency. lower latency compared to DigitalOcean for PostgreSQL. Now, let’s take a look at the throughput and latency performance of our comparison. Next, we are going to test and compare the latency performance between ScaleGrid and DigitalOcean for PostgreSQL. PostgreSQL DigitalOcean Latency Averages (ms).

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Zero Configuration Service Mesh with On-Demand Cluster Discovery

The Netflix TechBlog

Since there were no existing solutions available, we needed to build them ourselves. To improve availability, we designed systems where components could fail separately and avoid single points of failure. In this architecture, service to service communication no longer goes through the single point of failure of a load balancer.

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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

Within this paradigm, it is possible to run entire architectures without touching a traditional virtual server, either locally or in the cloud. In a serverless architecture, applications are distributed to meet demand and scale requirements efficiently. Every time the trigger executes, the function runs on an available resource.