Operations | Monitoring | ITSM | DevOps | Cloud

Looking at your IT environment, you probably have various machines and applications connected to your networks. From network devices to servers to laptops, you need to know what’s happening at all times. While your log data provides the monitoring information you need, your environment’s diversity makes aggregating and correlating this information challenging. If your company invested in Windows devices, then your struggle is even more real because Microsoft uses proprietary format.

The ability to manage IP addresses within a network is crucial for effective network management, especially as networks become more complex and have to manage more demanding loads. Assigning hundreds or even thousands of IP addresses to devices that may be highly distributed or disparate is no simple task. Once devices leave the network, those IP addresses may need to be deleted, plus there’s always the risk of IP address conflict.

IT leaders are thrilled about the potential of Generative AI for IT Operations. But they also want to know how it works, why it works, and what it will do for them before taking the leap and adopting this new technology. Allow me to share my perspective on the hype and the truth behind Generative AI. I’m the Field CTO for BigPanda, Operational Intelligence and Automation driven by AIOps.

The cloud’s elasticity—the ability to scale resources up and down in response to changes in demand—as well as variable cost structures offer significant advantages, enabling enterprises to move from rigid capex models to elastic opex models where they pay for what they provision, with engineers in control and focused on innovation, becoming true business accelerators.

It’s been another busy few months here at Gremlin. Overall, our team has been working on feature improvements to enable teams to measurably improve the reliability of their systems, whether that’s through broadening platform support so you can run Gremlin in more places, making it easier than ever to identify reliability risks, or improving reporting so you can manage reliability programs effectively at enterprise scale. Here’s a summary of what’s new.

Splunk is pleased to announce the general availability of Federated Search for Amazon S3, a new capability that allows customers to search data from their Amazon S3 buckets directly from Splunk Cloud Platform without the need to ingest it. Enterprises rely heavily on cloud object storage services as the de facto destination for their new data to leverage the cost, compliance, security, scalability and manageability benefits that cloud platforms can offer.

Imagine being able to foresee future trends, anticipate customer behaviour, optimize your operations, and take actions that are not just reactive — they shape the future of the market. In the world of data-driven decision-making, we're able to do all that by paying attention to the information we analyze from predictive and prescriptive analytics. A large and growing field, data analytics is often broken into four categories — of which predictive and prescriptive are two!

To successfully observe modern digital platforms, a new data collection approach was needed. And OpenTelemetry (OTel) was the answer - an industry-agreed open standard - not a single vendor's approach - on how observability (O11y) data should be collected from a platform. This separates out data collection from the vendors’ platform of data processing and visualisation, making the data collecting approach vendor agnostic.

In August, a ransomware attack hit another company. Unfortunately, it hit a regional cloud provider in Europe this time, and we can call this a “critical hit.” So far, we know a virtual server got compromised and used as a jump host; from there, the attacker started to encrypt all volumes in the same domain. Based on pure luck or some profound reconnaissance, the same server migrated into a different data center and continued its unplanned job from there.

The Oil and Gas sector, responsible in part for two industrial revolutions in the last 300 years, has been something of a laggard when it comes to adoption of new technologies. Cloud and edge penetration in Oil and Gas is late compared to other industries, mainly due to long standing concerns around security and data privacy.