For many businesses across the world, incident management is something that’s usually left to engineers. These teams are on the front lines, declaring, managing, and resolving all sorts of incidents across the org, regardless of where it originates or what form it takes. But there’s a glaring issue with this approach. Outside of technical teams, people across organizations aren’t accustomed or trained to use the word “incident” whenever an issue comes up.
In January of 2023, Google released its infrastructure reliability guide, which provides guidelines on how to build high-availability applications in Google Cloud. While it's written for Google Cloud, it provides some excellent general-purpose information on how to architect reliable applications on any cloud provider, including: In this blog, we'll explain each of these factors and how you can use Gremlin to ensure you're meeting your reliability requirements.
In data management, numerous roles rely on and regularly use telemetry data. The security engineer is one of these roles. Security engineers are the vigilant sentries, working diligently to identify and address vulnerabilities in the software applications and systems we use and enjoy today. Whether it’s by building an entirely new system or applying current best practices to enhance an existing one, security engineers ensure that your systems and data are always protected.
We’re surrounded by news of data breaches and companies being compromised, and the existential threat of ransomware hangs over just about every organisation that uses computers. One of the consequences is that we are hassled by an ever-increasing number of software updates, from phones and computers to vacuum cleaners and cars; download this, restart that, install the updates.
In an ideal world, organizations can establish a single, citadel-like data center that accumulates data and hosts their applications and all associated services, all while enjoying a customer base that is also geographically close. As this data grows in mass and gravity, it’s okay because all the new services, applications, and customers will continue to be just as close to the data. This is the “have your cake and eat it too” scenario for a scaling business’s IT.
As security becomes more advanced and available, companies must look for ways to be more efficient with their resources in order to stay competitive. With challenges that limit the capabilities of companies, such as limited employee resources and low customer tolerance for delays in services, reliable and affordable solutions are necessary. In this case, it means disrupting the traditional security industry. Organizations are achieving their goals by relying on automation and technology.
With one key practice, it’s possible to help your engineers sleep more, reduce friction between engineering and management, and simplify your monitoring to save money. No, really. We’re here to make the case that setting service level objectives (SLOs) is the game changer your team has been looking for.
The majority (83%) of employees across industries want their jobs to remain hybrid, Accenture reports. Yet nearly 50% of CIOs feel their cybersecurity initiatives aren’t keeping pace with their digital transformation efforts, according to research by ServiceNow and ThoughtLab. Neither are their cybersecurity budgets. Combining artificial intelligence (AI) and machine learning (ML) for IT operations (AIOps) can help.
