This article offers a comparison of two leading data analytics platforms: Sumo Logic and Splunk. It highlights the key factors to consider when choosing between these two options, including: functionality, scalability, deployment, security, cost, and licensing.

In essence, Splunk is suited for businesses with complex data needs and a preference for customization, while Sumo Logic caters more towards cloud-based log management and real-time data processing. The final decision depends on your specific requirements and budget.

Choosing a database is hard, however, maintaining it afterward is even harder. In this post, we talk about elements to focus on, tooling, monitoring, and other aspects of keeping the database up and running.

Databases are complex beasts. They have options for various areas like memory usage, backups, write-ahead-logs, monitoring, replication, and many more. Installing a database is just the beginning, we need to configure it accordingly later on to match our needs. In this blog post we cover the most important settings you should use.

Compares Prometheus and InfluxDB, two popular time series databases. It highlights the key differences between the two in terms of data model, query language, scalability, ecosystem, and pricing.

Here's a quick summary:

Data Model: Prometheus offers flexible querying with its multidimensional model, while InfluxDB is better for data retrieval with its tag-based model.

Query Language: Prometheus uses PromQL, InfluxDB uses InfluxQL (similar to SQL).

Scalability: Prometheus scales horizontally, InfluxDB scales vertically.

Ecosystem: Prometheus integrates well with monitoring tools, InfluxDB offers more integrations overall.

Pricing: Prometheus is free, InfluxDB has a free tier and paid tiers with more features.

Ultimately, the choice depends on your needs. Prometheus is ideal for monitoring and alerting with its flexible data model, while InfluxDB excels at handling large datasets.

This blog post offers a tutorial on launching multiple Amazon EC2 instances effortlessly using Terraform's count argument. It targets individuals new to AWS who want to create multiple EC2 instances or existing Terraform users looking to streamline deployments. The guide provides step-by-step instructions on setting up Terraform configuration files, defining variables, and running Terraform commands to launch the instances. It also covers verifying the deployment on the AWS console. Overall, the post highlights how Terraform simplifies managing and automating cloud infrastructure deployments.

The Virginia Department of Motor Vehicles proves that mainframes and DevOps can coexist, servicing millions of users while adopting agile development processes. Modernizing Adabas and Natural programming language allows the DMV to integrate with back-end services and automate testing. Despite cultur..

Back to the basics of Git...

Ever since the author started using Nix for development, the project relied on external services like databases and message brokers, leading to the use of Docker. However, to simplify the setup and reduce system resource consumption, the author decided to replace Docker with Nix in the project. A ne..

A GitHub engineer shared how GitHub Copilot helped in automating tasks like finding project dependencies and creating regular expressions. Using Copilot saved significant time on these tasks, making development more efficient. Other team members also shared how Copilot improved their workflows, from..

Boost software development productivity by 50x, as highlighted at AWS re:Invent expo. GenAI features focus on improving developers' productivity by reducing toil and costs. CodeWhisperer tool aims to enhance developer engagement and code quality, impacting team health and wellbeing metrics...