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Service level objective examples: 5 SLO examples for faster, more reliable apps

Dynatrace

Certain service-level objective examples can help organizations get started on measuring and delivering metrics that matter. Teams can build on these SLO examples to improve application performance and reliability. In this post, I’ll lay out five SLO examples that every DevOps and SRE team should consider. or 99.99% of the time.

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Monitoring Web Servers Should Never Be Complex

DZone

For example, you can monitor the behavior of your applications, the hardware usage of your server nodes, or even the network traffic between servers. For that reason, we use monitoring tools. And there are a lot of monitoring tools available providing all kinds of features and concepts.

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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

The control group’s traffic utilized the legacy Falcor stack, while the experiment population leveraged the new GraphQL client and was directed to the GraphQL Shim. This helped us successfully migrate 100% of the traffic on the mobile homepage canvas to GraphQL in 6 months. Correctness: The idea of correctness can be confusing too.

Traffic 358
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What is a service mesh?

Dynatrace

This becomes even more challenging when the application receives heavy traffic, because a single microservice might become overwhelmed if it receives too many requests too quickly. A service mesh enables DevOps teams to manage their networking and security policies through code. How service meshes work: The Istio example.

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Kubernetes vs Docker: What’s the difference?

Dynatrace

A standard Docker container can run anywhere, on a personal computer (for example, PC, Mac, Linux), in the cloud, on local servers, and even on edge devices. This opens the door to auto-scalable applications, which effortlessly matches the demands of rapidly growing and varying user traffic. Networking. Here are some examples.

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Dynatrace Managed turnkey Premium High Availability for globally distributed data centers (Early Adopter)

Dynatrace

For example, in a three-node cluster, one node can go down; in a cluster with five or more nodes, two nodes can go down. The network latency between cluster nodes should be around 10 ms or less. Minimized cross-data center network traffic. Automatic recovery for outages for up to 72 hours. Self-contained turnkey solution.

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Leveraging ML-Based Anomaly Detection for 4G Networks Optimization

DZone

Improving 4G Networks Traffic Distribution With Anomaly Detection Previous generations of cellular networks were not very efficient with the distribution of network resources, providing coverage evenly for all territories all the time.

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