Aryaka recently conducted a series of surveys in three distinct industries (manufacturing, transportation, and business services), looking deeper at key trends and pain points in networking and security. Despite differences in industry priorities and digital maturity, IT leaders in these sectors are all clearly facing an uphill battle to secure increasingly hybrid, cloud-connected, and distributed infrastructure without overwhelming their limited resources ...
Though migrating to the cloud offers myriad advantages over staying on-prem, there are some potential obstacles to be aware of. With thoughtful preparation and strategic implementation, you can navigate these hurdles to execute a seamless migration that makes the most out of your cloud investment. I've outlined some of the most common challenges below, as well as strategies for overcoming them ...
There's been a lot of talk lately about cloud repatriation ... Most organizations don't have the muscle memory or staffing to even attempt going back on-prem ... But there's more to the story. Because the question isn't just can we go back. It's should we — and if not, what should we do instead? ...
IT Asset Management (ITAM) has undergone significant transformations in response to the evolving IT landscape ... The rise of the cloud has introduced new complexities, such as the need to manage SaaS applications and maintain visibility into cloud assets. The integration of AI has further accelerated these changes, driving ITAM teams to collaborate more closely with other IT stakeholders ... This shift is essential for addressing the multifaceted challenges of modern IT environments ...
The observability landscape has transformed dramatically over the past decade. What began as traditional application performance monitoring (APM) has evolved into something more sophisticated and deeply essential to business operations. As we look at where the industry is headed, three themes have emerged that will define the future of how organizations monitor and manage their digital infrastructure ...
For years, IT Operations has been caught in a loop of reacting to incidents after they've already caused disruption. Even with monitoring, observability, and AIOps 1.0 (legacy AIOps solutions) in place, teams still face overwhelming alert volumes, fragmented data, and slow mean time to resolution (MTTR). The move to Predictive IT Operations offers a better path ...
Most teams go straight to the usual suspects when performance tanks in the cloud: app bugs, code regressions, maybe even the cloud provider itself. However, the real bottleneck is hiding in plain sight more often than not: the network ...
Your company's knowledge base is the engine that will power your AI agents. It's the structured data repository that an AI system uses to understand, reason, and make decisions ... Thus, transferring accurate knowledge is crucial. Incomplete or poor-quality data can reduce agent performance, accuracy, and even increase agent bias. Here are five steps to ensuring that your company's knowledge base transfer is optimal ...
The line between work and life is blurring faster than ever. A recent Microsoft study revealed that 40% of employees check emails before 6 a.m., and evening meetings have risen by 16% since the shift to remote work began. The result? A new phenomenon many are calling the "infinite workday." While the psychological toll of this always-on culture has rightfully received attention, there's another, often-overlooked dimension: its impact on IT performance, digital access, and user experience ...
Most teams collect observability data for the obvious reasons: uptime, latency, troubleshooting. It's the stuff we have to do to keep the lights on. But that mindset limits what this data is really capable of. When we treat logs like a transient utility instead of a long-term resource, we end up throwing away insight we can't get back. Losing that data isn't just a technical issue; it limits your ability to make smarter business decisions ...
JVM monitoring is crucial for java-based environments, to gain visibility into the performance and operations of VMs. It helps them understand the behavior of KPIs like memory and CPU utilization, threads, and garbage collection. These insights help administrators identify performance anomalies, locate erroneous corners in JVM environments, and fix ailments that cause issues like application downtime, unavailable services, data request saturation, and slow servers ...
Despite how critical digital experience can be for financial institutions, Catchpoint's 2025 Banking Website Performance Benchmark Report reveals a surprising reality: only 25% of global banks deliver homepage load times under three seconds. That means 75% are falling short of customer expectations ...
The next generation of AI is already here. It may have been mere months since organizations adopted generative AI (GenAI), but now there's a new kid on the block and it promises to offer even greater benefits to businesses and IT operations teams in particular ... The key to success will be to avoid repeating the adoption mistakes of the past and to start small with manageable projects ...
It's no secret that technology has transformed how industries approach workforce enablement and service delivery, and the public sector is no exception. Across federal, state, and local levels, government agencies are reassessing legacy systems and outdated processes with renewed urgency due to cybersecurity mandates, service disruptions and citizens' increasing expectations for digital access ...
The race toward AI maturity is on, but most enterprises are running uphill. According to new research from S&P Global Market Intelligence and Vultr, more than half of organizations expect to reach the "Transformational" stage of AI maturity by 2027 — a phase defined by widespread, embedded AI use across business operations. Yet as AI embeds deeper into real-time systems and mission-critical workflows, the gap between ambition and operational readiness is becoming harder to ignore ...
Adequately preventing and responding to disruptions has never been more important — or more possible. The growing ubiquity of AI has introduced more automated workstreams and increased productivity, while simultaneously creating a greater need for better data management. As customer expectations increasingly align with always-on services, the ability to prevent and recover from disruptions has direct ties to a business's bottom line ...
Enterprises are racing to leverage AI in their database environments — but most are skipping the guardrails. According to Quest research, 67% of organizations say AI is already critical to their database operations. Yet fewer than half report having a formal governance framework in place to manage it. That mismatch puts businesses at risk — operationally, financially, and reputationally ...
Microsoft's Windows 10 end of support is only several months away but new data shows enterprises still aren't feeling the urgency to migrate to Windows 11. The latest study data from ControlUp shows 50% of enterprise Windows endpoints still haven't completed Windows 11 migration ...
If you've worked in infrastructure or observability engineering for more than a few years, chances are you've been told more than once that practices like sampling, data aggregation, and short retention windows are just "best practices." The rationale is familiar: save money, reduce system strain, stay agile. But I want to challenge that framing. These aren't best practices. They're coping mechanisms. And they're costing us more than we realize ...
Apache Cassandra is loved for its scalability and flexibility. The capacity to handle large volumes of unstructured data and no single point of failure has made it a favorite among modern database solutions. But as functional as it may be, it comes with significant architectural complexity. Without complete visibility into your infrastructure, one blind spot can cause serious issues — downtime, or worse, critical app failures ...