Today's networks are driving more digital change than ever before, which is putting increased pressure on those responsible for deploying, monitoring and maintaining them. As a result, there's a premium on actionable real-time visibility into networks and application performance issues.
NetOps teams are now expected to proactively identify problems before they impact the organization, and if problems do arise, to solve them in real time to minimize the effects on the end user. The goal is to provide actionable network transaction-based monitoring, rapid root-cause analysis and integrated packet-level forensics in a single solution, so teams can quickly identify latency, communication and capacity issues.
However, extracting insight from the flood of information traveling through today's high-speed networks is a constant challenge faced by those responsible for network performance and reliability. Statistical summaries and aggregated data are traditionally just a starting point for further investigation into problems. And historically, packet data has not scaled for high-speed real-time monitoring. As a result, a new breed of solution has been born that simultaneously provides the precision of packet-based analytics with the speed of flow-based monitoring (at a reasonable cost).
The end result is actionable visibility, which helps teams focus on the biggest problem areas, which essentially requires four elements.
First, the data must be acquired from wire data, a datacenter, the cloud or the edge.
Next, the network and data must be monitored for end-user experience in true real time.
Third, the team must be ready to investigate a problem or issue, from traffic to trace files.
And finally, a certain level of the packet data must be retained so teams can troubleshoot. How can this level of network visibility be put into action?
Here are 6 reasons to use these new NPM/APM analytics solutions:
1. Find out quickly if it's the application or the network
When problems emerge, you need to solve them fast. Understanding if this is an application or a network issue – and having the packet data to back up that claim – is critical to eliminating debates and war room discussions.
For example, see at a glance which transactions on the networks are experiencing the worst network and the worst application latency, from network-wide down to an individual server. When you see application latency that is outside of the norm, a single click can provide the actual packet data comprising the network transaction. This is the best data possible for determining the root cause of the problem. Often times application errors can quickly be identified in the packet payload data.
2. Gain visibility into the line of business
For many companies, the business is the application(s) they run. For example, an online retailer is defined by the performance of the web servers and associated web applications driving the storefront. Visibility into key performance indicators for these specific applications, including network and application latency and transaction quality for each and every transaction, drives real-time response that keeps the storefront running at its maximum potential.
3. Speed to resolution
Every second counts when the network or an application has a problem. Having the ability to navigate fluidly in real-time at up to 35 Gbps of network traffic, and then immediately click through to specific packet data dramatically speeds resolution time. Plus, the less time the network team or IT spends troubleshooting, the more time they can spend on projects to improve the network, like cloud migrations or building data warehouses.
Read 6 Reasons Every NetOps Team Should Use a Packet-Based Analytics Solution - Part 2 for 3 more reasons to use the new NPM/APM analytics solutions.
The Latest
From the accelerating adoption of artificial intelligence (AI) and generative AI (GenAI) to the ongoing challenges of cost optimization and security, these IT leaders are navigating a complex and rapidly evolving landscape. Here's what you should know about the top priorities shaping the year ahead ...
In the heat of the holiday online shopping rush, retailers face persistent challenges such as increased web traffic or cyber threats that can lead to high-impact outages. With profit margins under high pressure, retailers are prioritizing strategic investments to help drive business value while improving the customer experience ...
In a fast-paced industry where customer service is a priority, the opportunity to use AI to personalize products and services, revolutionize delivery channels, and effectively manage peaks in demand such as Black Friday and Cyber Monday are vast. By leveraging AI to streamline demand forecasting, optimize inventory, personalize customer interactions, and adjust pricing, retailers can have a better handle on these stress points, and deliver a seamless digital experience ...
Broad proliferation of cloud infrastructure combined with continued support for remote workers is driving increased complexity and visibility challenges for network operations teams, according to new research conducted by Dimensional Research and sponsored by Broadcom ...
New research from ServiceNow and ThoughtLab reveals that less than 30% of banks feel their transformation efforts are meeting evolving customer digital needs. Additionally, 52% say they must revamp their strategy to counter competition from outside the sector. Adapting to these challenges isn't just about staying competitive — it's about staying in business ...
Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey ...
SLOs have long been a staple for DevOps teams to monitor the health of their applications and infrastructure ... Now, as digital trends have shifted, more and more teams are looking to adapt this model for the mobile environment. This, however, is not without its challenges ...
Modernizing IT infrastructure has become essential for organizations striving to remain competitive. This modernization extends beyond merely upgrading hardware or software; it involves strategically leveraging new technologies like AI and cloud computing to enhance operational efficiency, increase data accessibility, and improve the end-user experience ...
AI sure grew fast in popularity, but are AI apps any good? ... If companies are going to keep integrating AI applications into their tech stack at the rate they are, then they need to be aware of AI's limitations. More importantly, they need to evolve their testing regiment ...
If you were lucky, you found out about the massive CrowdStrike/Microsoft outage last July by reading about it over coffee. Those less fortunate were awoken hours earlier by frantic calls from work ... Whether you were directly affected or not, there's an important lesson: all organizations should be conducting in-depth reviews of testing and change management ...