Operations | Monitoring | ITSM | DevOps | Cloud

There is a question a lot of engineering leaders are quietly sitting with right now: we have rolled out AI tools across the team, the developers seem faster, so why isn't more software actually shipping? It is a reasonable thing to consider. Pull requests are opening faster. Lines of code per sprint are up. The boilerplate that used to take full afternoons now takes minutes. By every local measure, the investment is paying off.

The GitHub Copilot cost runs from $0 for the Free tier to $10/month for Pro, $39/month for Pro+, and $100/month for Max. Teams pay $19/user/month for Business and $39/user/month for Enterprise. The twist: on June 1, 2026 GitHub swapped fixed premium requests for usage-based AI Credits, so what those flat fees actually buy now depends on how hard you push the AI. The sticker price is the easy part. The part that ambushes finance is everything stacked on top of it.

The controls at the top of Explorer are great for a simple question. But as your query grows with more group-bys or a stack of filters, those controls start eating into the vertical space you actually want for your data. Now you have the option to move filters and groupings into a dedicated left side panel, so a complex query has room to scale cleanly. Set it once and CloudZero keeps it that way.

Standardizing the fleet: automated updates for multi-site management There's a specific kind of update that Drupal agencies and enterprise teams dread: a security release in something the whole fleet runs on, the PHP runtime, the database engine, or a shared service, with a patched version available now and a deadline attached. For a team managing a single site, moving to the patched version is an afternoon of work.

Modernization assessments move faster when the structure is already in place. Instead of recreating custom fields, interview questions, and assessment workflows for every customer, you can use a custom field template to standardize how data is collected from the start. This guide shows you how to create a reusable Tidal Accelerator custom field template using Node.js and the Tidal API, so your assessments are easier to repeat, compare, and scale. So you’re starting a modernization practice.

"Hello world, this is your agent speaking!" The agent loop! The LLM is calling tools, the answers are sensible, and the sky's the limit. Now, as you look forward to production, you look for a composable toolset, something that can grow with your use case and system needs. That's what we created with Honeycomb Canvas: a collaborative investigation space where AI agents help you understand, fix, and learn about your system.

GPT-4 API pricing spans $0.10 to $30.00 per million input tokens across the model family. GPT-4.1 is the current recommended production model at $2.00 input / $8.00 output per million tokens. Legacy GPT-4 still runs at $30.00/$60.00 per million tokens -- 15x more expensive for no meaningful quality gain. For finance and engineering leaders accountable for AI spend, choosing the right GPT-4 variant is the single biggest cost lever on your bill.

Three ways to archive a shared mailbox: In-Place Archive (licence rules), inactive mailbox retirement, or archiving departed-user mail before converting.