A new IDC report reveals the worldwide APM market grew by 13% in just one year, indicating application performance is increasingly critical in the digital world. In this IDC report, you’ll gain insights into:
- What factors are contributing to the increasing rate of growth in the APM market
- Significant market trends and recent developments to help guide your APM strategy
- Why AppDynamics is the largest APM provider and the fastest growing
Cory Watson has been immersed in the practice of Observability for nearly a decade from one of the first hires to Twitter’s embedded SRE program to the Observability team lead at Stripe. Now a Technology Director in the office of the CTO at SignalFx, Cory has written an insightful eBook that shares his successes and failures in creating and managing Observability teams. In this eBook, you’ll get a better understanding of Observability — why it’s important, what to expect, and how to get started. This eBook covers:
- What Observability is and isn't
- The difference between Monitoring and Observability
- Why Observability is critical in the cloud-native era
- How you can get started with Observability
Today's IT environments are exploding in complexity,ty, reducing visibility across the technology stack. But with an AIOps mindset — and an AI-powered APM solution — organizations can drive cross-domain visibility, insights and automation to deliver an exceptional customer experience. Get the use case guide to find out how other IT teams are using the Central Nervous System (CNS) for IT to support intelligent auto-scaling, automatic workload optimization, and network triage. Gain insights into:
• What the CNS is — and how it's ignited a new era of AIOOps
• The three core pillars upon which the CNS is built
• How companies like yours are using the CNS platform
Application environments have exploded in complexity, making them too dynamic for IT teams to manage manually. Read this report to learn how organizations are leveraging AI to help manage the volume of data within the IT ecosystem.
Delivering optimal end-user experiences is critical in today's digital world. But the sheer complexity of modern applications often puts performance in jeopardy. See how you can side-step slow-downs and eliminate obstacles to application performance.
Discover how the marriage of artificial intelligence, machine learning, and analytics enables companies like FedEx to accelerate issue resolution and improve business outcomes.
In this Harvard Business Review Analytic Services study you’ll learn what the most successful companies are doing differently in terms of how they assess and improve their customer experience (CX) apps.
Discover tried-and-tested strategies for future-proofing your application environment—all rooted in the real-world experiences and successes of today’s most progressive IT leaders.
Autonomous Operations is all about applying more intelligent automation to scale IT incident management, optimize your operational costs, improve service availability and mitigate the risks of digital transformation. Powered by machine learning, Autonomous Operations is the next generation, evolving beyond everything that has come before: from legacy ECA to AIOps. Download this eBook to learn all about what Autonomous Operations is, the problems it helps solve, what makes it “autonomous”, and the capabilities of BigPanda – the first Autonomous Operations solution available.
Artificial Intelligence (AI) may no longer be a revolutionary term, but for such a transformative and critical piece of technology, it often remains poorly understood by the teams that need it most. The new field of AIOps aims to narrow that gap for today’s leaders in IT Ops. AIOps offers critical capabilities to bring calm to overwhelmed IT Ops, NOC and DevOps teams and mitigates the fallout from today’s complex, noisy and dynamic IT stacks. This CIO Dive playbook explains how adopting AIOps can stem digital transformation’s deluge of work and give IT Ops leaders and decision makers pivotal insights otherwise unavailable.
IT operations is a battle with complexity — and IT operations and NOC teams are losing. This executive brief shows how tool proliferation and IT operations noise drive up headcount and force IT operations teams into a reactive mode that increases costs and decreases customer satisfaction. But now AI and machine learning (ML) enable autonomous operations that cuts through the noise to identify developing problems and their root cause before they impact services. That reduces outages and their durations and allows operations and NOC staff to focus on the most critical problems. Read the executive brief to learn how BigPanda enables IT operations to address overwhelming noise.
Stretched thin and relying on legacy IT Ops tools, IT Ops, NOC and DevOps teams are unable to effectively support today’s highly complex, dynamic IT stack. This is causing a rising tide of outages, poor app performance and service disruptions. Download this whitepaper by noted industry analyst Nancy Gohring from 451 Research, to learn how AI and ML-driven IT Ops automation can help.
According to CNCF’s 2018 survey, 73% of respondents indicated they are currently using containers in production to boost agility and speed up the rate of innovation. But operating container-based environments also has its challenges. In the same CNCF survey, the majority of respondents also cited monitoring as their number one concern for adopting containers. This white paper will walk you through important decisions before implementing containers in production.
Today, teams across the enterprise are building and managing large-scale, data-driven applications to drive value for their business – including IT operations, app developers, data scientists, and data engineers. But, getting optimal performance from your data applications is both challenging and expensive. Read this guide to learn how to:
- Remove performance blind spots in your data applications
- Better allocate resources and reduce costs
- Automatically tune performance
Download the Gartner Magic Quadrant for Application Performance Monitoring 2019 to get insight into:
- Application Performance Monitoring market overview
- Gartner's evaluation criteria
- Evaluations of each recognized vendor
- Latest trends in APM landscape
Get this complimentary white paper on JVM performance management and learn tips and best practices for:
- Diagnosing a runaway Java application and identifying a high CPU thread which is the root cause
- Troubleshooting a hung Java application and isolating the blocked thread that is causing the problem
Take control of your Java applications and ensure supreme digital experience for your users.
Riverbed Technology has been recognized as a Leader in the Gartner Magic Quadrant for Network Performance Monitoring and Diagnostics (NPMD) for the sixth year in a row. Register to view your complimentary copy of the full 2019 report, which includes:
- Growth of the NPMD market
- Gartner's latest criteria for a fully-equipped NPMD solution
- The NPMD vendor landscape
- Key NPMD trends
This Definitive Guide to Serverless Monitoring and Observability shares lessons learned from dozens of SignalFx customers using serverless in production. The Guide focuses on three new ways to think about serverless monitoring and observability, and explains how SignalFx is architected to meet those criteria. In this guide you’ll learn about:
- Serverless architectures
- The benefits of leveraging serverless in your environment
- The key challenges for monitoring serverless environments
- The new criteria for serverless monitoring and observability
- The top five FaaS metrics to monitor
- How SignalFx monitors serverless at scale
Today’s software-centric business models have completely changed competitive dynamics, opening up opportunities for disruption across every industry. Speed of innovation and the ability to operate in real-time have become critical capabilities for every organization. Companies have to rethink how they monitor their infrastructure, applications, and the performance of their business. SignalFx's founding technical team figured out how to monitor at scale at Facebook during their move fast and break things days -- the precursor to DevOps today. In this whitepaper, you’ll get a glimpse into what the SignalFx team learned, and how that led them to create the only cloud monitoring solution built on a streaming architecture. In this whitepaper, you’ll learn:
- How companies are using software to speed up innovation and stay competitive
- The three stages that companies typically go through to become cloud-native
- New requirements and challenges for monitoring today’s cloud-native architectures
- Why a monitoring platform with a streaming architecture is the only way to operate in real-time at any scale