Welcome to 2023! The year of the Linux Desktop, the rise of AI, Software Bill of Materials (SBOM), DevOps is Dead, Platform Engineering is Alive, and a CNCF landscape that won’t be getting any simpler! Seriously, the technology and software sector is growing at a faster pace than any time I can ever recall. Where do we even begin? I hope you enjoy some predictions and trends that will become more and more evident in 2023.
For many businesses, prioritizing reliability is an ongoing challenge. Building reliable systems and services is critical for growing revenue and customer trust, but other initiatives—like building new products and features—often take precedence since they provide a clearer and more immediate return. That's not to say reliability doesn't have clear value, but proving this value to business leaders can be tricky.
Azure Blob storage has several storage tiers that offer different performance and cost characteristics. The storage tiers available are: Customers can move data between these tiers based on their access patterns, which can help reduce costs while still meeting performance requirements.
Recording rules is a clever concept introduced by Prometheus for storing results of query expressions in a form of a new time series. It is similar to materialized view and helps to speed up queries by using data pre-computed in advance instead of doing all the hard work on query time. Like materialized views, recording rules are extremely useful when user knows exactly what needs to be pre-computed. For example, a complex panel on Grafana dashboard or SLO objective.
A few years ago, the school’s technical support could still cope with its tasks. Help with technology in the classroom, maintenance of educational platforms, statistics, accounting – all these were difficult, but it was still possible to handle a few people and the IT department of the school. But the pandemic has shown how educational institutions, from elementary schools to universities and academies, need more time to be ready for large-scale work in the digital space.
Data visualizations take complex information and present it in a clean and easy-to-understand visual. Done right, they can allow quick insight through easy pattern and outlier recognition. Done wrong, it can confuse, obfuscate, and lead to wrong conclusions. Yikes! Over the past few months, we've been hard at work modernizing Honeycomb’s data visualizations to address consistency issues, confusing displays, access to settings, and to improve their overall look and feel.
