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Five-nines availability: Always-on infrastructure delivers system availability during the holidays’ peak loads

Dynatrace

The nirvana state of system uptime at peak loads is known as “five-nines availability.” In its pursuit, IT teams hover over system performance dashboards hoping their preparations will deliver five nines—or even four nines—availability. How can IT teams deliver system availability under peak loads that will satisfy customers?

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

which is difficult when troubleshooting distributed systems. Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Investigating a video streaming failure consists of inspecting all aspects of a member account.

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What is infrastructure monitoring and why is it mission-critical in the new normal?

Dynatrace

IT infrastructure is the heart of your digital business and connects every area – physical and virtual servers, storage, databases, networks, cloud services. We’ve seen the IT infrastructure landscape evolve rapidly over the past few years. What is infrastructure monitoring? . Dynatrace news.

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Visual Network Mapping Your K8s Clusters To Assess Performance

DZone

Building performant services and systems is at the core of every business. Tons of technologies emerge daily, promising capabilities that help you surpass your performance benchmarks. Growing organizations, in the process of upscaling their services, unintentionally introduce complexities into the system.

Network 300
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Comparing Approaches to Durability in Low Latency Messaging Queues

DZone

A significant feature of Chronicle Queue Enterprise is support for TCP replication across multiple servers to ensure the high availability of application infrastructure. This is the first time I have benchmarked it with a realistic example. Little’s Law and Why Latency Matters.

Latency 275
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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. See more fault recovery experiments and insights in our full paper.

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Why Tcl is 700% faster than Python for database benchmarking

HammerDB

Python is a popular programming language, especially for beginners, and consequently we see it occurring in places where it just shouldn’t be used, such as database benchmarking. We use stored procedures because, as the introductory post shows, using single SQL statements turns our database benchmark into a network test).