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The Ultimate Guide to Database High Availability

Percona

Defining high availability In general terms, high availability refers to the continuous operation of a system with little to no interruption to end users in the event of hardware or software failures, power outages, or other disruptions. Failure detection : Monitoring mechanisms detect failures or issues that could lead to failures.

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High Availability vs. Fault Tolerance: Is FT’s 00.001% Edge in Uptime Worth the Headache?

Percona

Some of the most important elements include: No single point of failure (SPOF): You must eliminate any SPOF in the database environment, including any potential for an SPOF in physical or virtual hardware. Failure detection: Monitoring mechanisms detect failures or issues that could lead to failures. What is fault tolerance?

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The Return of the Frame Pointers

Brendan Gregg

It was also a virtual machine that lacked low-level hardware profiling capabilities, so I wasn't able to do cycle analysis to confirm that the 10% was entirely frame pointer-based. Enterprise environments are monitored, continuously profiled, and analyzed on a regular basis, so this capability will indeed be put to use.

Java 145
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HammerDB v4.3 New Features Pt1: Graphical Metrics for PostgreSQL

HammerDB

This enables the user to compare and contrast performance across different benchmark scenarios. By clicking on the Metrics Display option, HammerDB will connect to the target database and start monitoring the performance, note that if the pg_active_session_history table is empty the viewer will report an error and refuse to start.

Metrics 62
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HammerDB v4.0 New Features Pt1: TPROC-C & TPROC-H

HammerDB

A full understanding of why this is important requires some knowledge of the evolution of database hardware and software. The HammerDB TPROC-C workload by design intended as CPU and memory intensive workload derived from TPC-C – so that we get to benchmark at maximum CPU performance at a much smaller database footprint.

C++ 40
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What Adrian Did Next?—?Part 2?—?Sun Microsystems

Adrian Cockcroft

I became the Sun UK local specialist in performance and hardware, and as Sun transitioned from a desktop workstation company to sell high end multiprocessor servers I was helping customers find and fix scalability problems. We had specializations in hardware, operating systems, databases, graphics, etc. that a lot of people used.

Tuning 52
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Kubernetes for Big Data Workloads

Abhishek Tiwari

Containerized data workloads running on Kubernetes offer several advantages over traditional virtual machine/bare metal based data workloads including but not limited to. support for logging, monitoring, and observability. In fact, if we go by current trends containerised microservices running on Kubernetes are the future.