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10 tips for migrating from monolith to microservices

Dynatrace

Transforming an application from monolith to microservices-based architecture can be daunting, and knowing where to start can be difficult. Unsurprisingly, organizations are breaking away from monolithic architectures and moving toward event-driven microservices. Migration is time-consuming and involved. create a microservice; 2.

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How To Scale a Single-Host PostgreSQL Database With Citus

Percona

PostgreSQL Cluster One coordinator node citus-coord-01 Three worker nodes citus1 citus2 citus3 Hardware AWS Instance Ubuntu Server 20.04, SSD volume type 64-bit (x86) c5.xlarge And now, execute the benchmark: -- execute the following on the coordinator node pgbench -c 20 -j 3 -T 60 -P 3 pgbench The results are not pretty.

Database 102
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The top 5 reasons to run your own database benchmarks

HammerDB

Some opinions claim that “Benchmarks are meaningless”, “benchmarks are irrelevant” or “benchmarks are nothing like your real applications” However for others “Benchmarks matter,” as they “account for the processing architecture and speed, memory, storage subsystems and the database engine.”

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The evolution of single-core bandwidth in multicore processors

John McCalpin

I have a lot of historical data using my ReadOnly benchmark (as described in some of the earliest entries in this blog [link] A read-only access pattern removes the need to understand and explain the many complexities associated with the “streaming stores” typically used in the STREAM benchmark (e.g., Stay tuned!

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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.

Tuning 52
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Is It a Read Intensive or a Write Intensive Workload?

Percona

Because recognizing if the workload is read intensive or write intensive will impact your hardware choices, database configuration as well as what techniques you can apply for performance optimization and scalability. Let’s examine the TPC-C Benchmark from this point of view, or more specifically its implementation in Sysbench.

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Why MySQL Could Be Slow With Large Tables

Percona

There are a couple of blog posts from Yves that describe and benchmark MySQL compression: Compression Options in MySQL (Part 1) Compression Options in MySQL (Part 2) Archive or purge old or non-used data: Some companies have to retain data for multiple years either for compliance or for business requirements.