“50% of enterprises will be actively adopting AI to augment their application performance monitoring (APM) tools in order to catch incidents before they become critical. Most APM existing tools offer limited context, leaving site reliability engineers without a way to effectively leverage insights and improve revenue, risk and cost. AI’s ability to recognize patterns and made predictions set it up as the perfect tool to bridge the gap.”
Artificial Intelligence at the core of your approach to application-centric IT enables your SRE teams to simplify, automate and prioritize work—and exploit opportunities to accelerate and automate incident management and resolution. This results in more opportunities and time to focus on valuable talent on delivering new initiatives and higher value to users.
Enterprises are in a can’t lose race to deliver increasingly valuable digital experiences to their customers and employees to succeed in their markets and retain talent. To stay competitive, CIOs and their teams are shifting to the site reliability engineering (SRE) operating model to ensure the resiliency and robustness of applications while teams simultaneously and rapidly deliver innovative new features to customers.
But even the most mature SRE teams face challenges, especially with the rapidly proliferating data created by hybrid cloud and cloud-native technologies. Teams are responsible for dynamic and complex applications, often across multiple cloud environments. SREs have to build understanding from a myriad of different tools and signals as they work to proactively understand, resolve and prevent problems such as meeting service level metrics, downtime and outages.
SRE teams are evaluating more intelligent IT operations to help address these challenges, including the adoption of AI and automation to help improve incident management and resolution. These questions can help explore the opportunities to exploit AI to automate your incident management:
AI and machine learning (ML) have emerged as a means to relieve the manual toil associated with the challenging SRE role and free teams to focus on highvalue work and innovation.
The initial promise of AI is fast becoming reality. SRE teams are starting to apply AI to create intelligent IT operations as ML models reliably detect patterns and build insight from past experience. AI and automation applied to operations, AIOps, helps teams manage the vast volumes of data and achieve proactive incident resolution.
Enterprises across industries are excited about AIOps as a means to:
A single, intelligent and automated IT operations platform infused with AI supports converging DevSecOps practices in an open, hybrid cloud environment so your teams can freely collaborate. An application-centric view accelerates effective collaboration across different roles responsible for a service, whether performed by a single person or multiple teams. AIOps powers shared context across user experiences with ChatOps dashboards and, by embracing a team’s chosen tools for problem-solving and understanding the context of an incident, allows SREs to move faster and collaborate to diagnose, fix and prevent incidents.
An application-centric approach facilitates integrated security and compliance by design and across DevSecOps processes to meet client service level objectives (SLOs) or privacy rules. Enabling policydriven deployments and integrated compliance assessments builds an automated governance,
risk and compliance posture into your DevSecOps workflows.
Powered by innovations from IBM Research, IBM Cloud Pak® for Watson AIOps empowers your SREs and IT operations teams to move from a reactive to proactive posture towards application-impacting incidents. It gives you the tools to place AI at the core of your IT operations. With the Cloud Pak for Watson AIOps, you can use AI across every aspect of your IT operations toolchain to improve resiliency and efficiency. It’s consumable on your cloud of choice or preferred deployment option.
The Cloud Pak for Watson AIOps provides a holistic view of your applications and IT environments by synthesizing data across siloed IT stacks and tools so you can resolve complex issues. The solution uses ML and natural language processing (NLP) to correlate structured and unstructured data in real time, allowing SRES to uncover hidden insights, diagnose causes and identify resolutions faster.
Augmenting your preferred toolchain with AI unlocks opportunities to use best-in-class monitoring, alerting and collaboration tools to work more efficiently and improve operational efficiencies.
The Cloud Pak for Watson AIOps uses pre-built AI models tuned by data from your applications to give valuable new insights specific to your environments. The solution identifies and gathers signals across a variety of structured and unstructured data channels and eliminates the need for time consuming contextswitching between tools and dashboards. Insights and recommendations are proactively delivered within your team’s existing ChatOps workflow or other preferred collaboration experience.
AI at the core of your approach to application-centric IT enables your SRE teams to simplify, automate and prioritize work—and exploit opportunities to accelerate and automate incident management and resolution. This results in more opportunities and time to focus on valuable talent on delivering new initiatives and higher value to users.
The Cloud Pak for Watson AIOps monitors incoming data feeds including logs, metrics, alerts, application topologies and tickets, highlighting potential problems by connecting the dots across data silos. It gives SREs the insights where they work, allowing them to understand the data, apply context across all workflows and automate problem resolution from a single source of truth.
Explore how applying AI and automation to IT operations can help SREs ensure resiliency and robustness of enterprise applications and free valuable time and talent to support innovation.
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Source: IBM
Cloud integration is a set of solutions and technology that integrates several cloud environments, applications, or systems to allow for real-time data and process interchange.
Cloud Integration is combining various cloud-based systems to make a single infrastructure. It can also be known as Hybrid cloud, cloud system integration, cloud data integration.
Businesses are now getting fascinated by automation and technological advancement. & why should they not? If a company wants to grow more prominent after a certain point,
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