Operations | Monitoring | ITSM | DevOps | Cloud

Best Salesforce ODBC Connector Tools in 2026

Salesforce ODBC drivers solve a specific problem: they allow SQL-based tools to query Salesforce data without requiring custom API integrations. That capability matters because Salesforce holds over 20% of the global CRM market and is used by more than 150,000 companies worldwide, making it the largest CRM ecosystem in operation today.

Introducing Application Metrics: Track the signal, see the spike, jump to the trace

A few weeks ago we had a bug with Session Replay. Replays were failing in some browsers once more than 1,000 video segments loaded. We had no idea how often it happened or who was hitting it, and because the failure didn’t always produce an error, we had no way to find affected users to reproduce it. Before, we could’ve answered this with spans or logs, but it’s clunky — spans are often sampled, so you can miss outliers; logs are less structured and tend to change over time.

ActiveMQ JMS 2.0 Implementation Guide: Simplified API, Transactions & Spring

For most of JMS's lifetime, writing a simple producer required creating a ConnectionFactory, creating a Connection, starting it, creating a Session, creating a MessageProducer, creating a Message, calling send(), and then closing the producer, session, and connection with the close calls safely wrapped in finally blocks to prevent resource leaks. Every developer knew the pattern. Every developer wrote it slightly differently. Every code review had the same comments about resource management.

Introducing the Coralogix CLI: Headless Observability for Every Agent

This article is a high-level overview of the Coralogix CLI. For a deeper look at how it works in practice, read the full technical deep dive here. Agent-driven investigation sounds simple: read the alert, query the data, return the cause. In reality, most agents either overload their context window with raw logs or guess at queries and return incorrect results.

Calculating The Kubernetes Integration Tax: What Your DIY Networking Stack Actually Costs

It was 11:47pm on a Thursday night, and a senior platform engineer at a large North American bank was rolling back a ‘simple’ configuration change. The change itself was small, a routine update approved through the usual review process, but when it was applied, pods began cycling and connections started dropping. For the next three seconds, mobile banking sessions already mid-transaction dropped. Customer support lit up.

The boring 80% is what kills your backlog

A few weeks ago, we shipped cascading replication for PostgreSQL, MySQL and Redis on Cloud 66. Customers can now build replication chains: a primary streaming to a middle replica, which in turn streams to leaves. It reduces load on the primary, supports geographic distribution, and stops you from melting your network when you have a large fan-out of replicas all pulling WAL from the same machine. PostgreSQL has supported cascading replication natively since version 9.1, which shipped over a decade ago.

The AI Paradox: Why You Have To Spend More And Can't Explain Where It Goes

AI adoption costs are going parabolic. The companies that can see what they're spending will invest with confidence. Everyone else is flying blind. Every company adopting AI is facing the same problem: the cost of AI adoption in products, in operations, and especially in engineering is accelerating with no alignment between spend and value. The competitive pressure is real. Companies that don’t invest in AI will be displaced by those that do. But the investment itself is becoming inscrutable.

SmartAssist and SQL Analytics - AI-powered querying

SQL Analytics has always been one of my favourite SquaredUp features. That's not just because I can use raw SQL to achieve complex data transformations. The fact that I can run SQL queries over data from all sorts of sources — not just relational databases, gives incredible power and flexibility. The great news is that SQL Analytics now ships with our AI-driven SmartAssist technology.