While application performance monitoring can provide us with metrics on software use and delays, SolarWinds® Database Performance Monitor (DPM) was built to tell us stories as to why user behavior is the way it is in the database. Database performance monitoring for developers in the distributed cloud industry is an important practice for maintaining the best environment for your users.
Imagine some users complaining that querying PostgreSQL is slow (this never happened right?), and we have to troubleshoot this problem. It could be one of two things: I would normally first check on the environment, specifically PostgreSQL metrics over time. Such monitoring shows if the CPU is too high or how many disk reads were buffer reads. PostgreSQL logs also give information about the environment, such as how many statements were run and if any errors occurred.
Evolving MySQL operations requires understanding how MySQL works. A good monitoring tool alerts on issues before they impact end users and helps reduce the MTTR of incidents when they do occur. But choosing a database monitoring solution can be tough due to the vast number of solutions available, each with their own pros and cons. In this blog post, I’ll review some of the best MySQL monitoring tools available that can help measure and improve database performance.
Data is often stored in a distributed manner — spread across many locations and even several clouds. Consolidating your data into a single data warehouse or data lake can be very difficult and expensive, particularly when data is housed in multiple cloud platforms. The problem of data consolidation becomes extremely expensive, too, when platforms charge egress fees for data transfers.
A large amount of data requires special tools. Apache Cassandra is one of those databases that can handle a large amount of data spread among many commodity servers, providing high availability and fault tolerance without a single point of failure. Developed under the umbrella of Apache Software Foundation, it ensures full visibility into the code base and being free of charge.
MarkLogic is a multi-model NoSQL database with support for queries across XML and JSON documents (including geospatial data), binary data, and semantic triples—as well as full-text searches—plus a variety of interfaces and storage layers. Customers include large organizations like Airbus, the BBC, and the U.S. Department of Defense. Because MarkLogic can process terabytes of data across hundreds of clustered nodes, maintaining a deployment is a complex business.
For the last few months, I have been actively contributing to the InfluxDB community by building InfluxDB Templates for InfluxDB 2.0. InfluxDB is the purpose-built time series database used for metric collection and storage. Let’s build an InfluxDB Template to monitor PostgreSQL together! 👏
Our goal is to support both MySQL and PostgreSQL as a backend wherever we need a database. Our latest addition in this area was PostgreSQL support for reporting, which will be released in the next few weeks. We don’t have PostgreSQL support for Icinga Certificate Monitoring yet. But it has already been worked on and the pull request for it is waiting to be tried. We would be happy to receive feedback in this regard so that we can fully merge PostgreSQL support as soon as possible.