Operations | Monitoring | ITSM | DevOps | Cloud

Artificial Intelligence (AI) is rapidly becoming an essential component of the telecommunications industry, driving significant changes in how networks are managed, optimized, and maintained. With the growing complexity of telecom networks, coupled with the rising demand for seamless connectivity, AI offers a range of solutions to address these challenges. From predictive maintenance and network optimization to enhancing customer service, AI is poised to transform telecom operations.

DevOps practices have become essential for streamlining the journey from code to production. Development and operations teams work together to ship better software faster. But even with DevOps, getting source code from commit to production can face long lead times and scalability issues. That's where deployment pipelines come in, automating the journey and speeding processes up. In this article, we’ll walk you through automating your deployment pipeline.

It’s 2 am on a Saturday, you’re sound asleep, and suddenly your phone lights up, ringing and buzzing loudly on your nightstand. You know it won’t be good news, but it’s worse than you could have imagined—your network and systems have suffered a ransomware attack. As you quickly change and start driving into the office, you keep asking yourself one question—didn’t we pass our annual security audit three months ago with flying colors?

This guide covers types of data that can be redacted and step-by-step instructions for configuring the Attribute Processor.

Steve Jobs once said that giving customers what they wanted wasn’t his approach. “Our job is to figure out what they're going to want before they do,” he said instead. “People don't know what they want until you show it to them. Our task is to read things that are not yet on the page.” By now, this wisdom has become canonical for companies targeting end-users, but we tend to ignore it when we’re building products and processes for professional users.

The Cyber Resilience Act (CRA) is nearly upon us. This wide-reaching piece of legislation will introduce new requirements, checks and balances on developers, retailers and device manufacturers; many of the looming demands haven’t gone down well in the open source community.

Gartner predicts that by the end of 2025, 80% of organizations will use cloud automation tools to orchestrate workloads. The firm also forecasts that spending on public cloud services will hit $679 billion by the end of 2024, with SaaS leading the cloud computing market. This surge in cloud spending will shape the future of SaaS, and cloud automation tools will play a key role in this transformation.

Many SaaS companies struggle to get engineers to take charge of costs and lower cloud expenses. Confused business leaders often put the problem on the shoulders of the engineers: Surely, it’s just that the engineers don’t care enough to stay within budget, or maybe they just don’t want to participate in the culture of cost efficiency leadership is trying to build. But what if your engineers actually do want to optimize costs—they just don’t have the tools and data to do so?

There’s a major outage. Support tickets are mounting. Everybody from engineering to legal is scrambling for information. You have more Teams notifications clamouring for attention than you do minutes to address them, and it’s hard to know where to begin. What comes next is a balancing act—mitigating the impact, updating colleagues, managing action items, or updating a status page that will be seen by millions.