OpsRamp now supports more than 2,500 integrations with other technologies, covering virtually every commonly used technology in MSP and enterprise IT environments.
These integrations include cloud and hybrid infrastructure environments which OpsRamp monitors, such as Amazon Web Services, Microsoft Azure, Google Cloud, Cisco and VMware, as well as other IT operations management tools with which OpsRamp interacts and exchanges data, such as ServiceNow, Splunk and Datadog.
This extensive integration library allows OpsRamp customers and partners to consolidate IT operations management tools at their own pace. OpsRamp can either replace legacy tools or use them as data sources in more of a manager of managers role, integrating and correlating metrics and events from multiple monitoring tools.
“OpsRamp is built to work with all of our customers’ existing point tools and hybrid IT infrastructure,” said Varma Kunaparaju, OpsRamp CEO. “Whether you are replacing legacy tools or trying to integrate your events and performance metrics with your newer cloud monitoring tools, we can support you on your journey to modernize IT operations management with AIOps. Our extensive integration support shows just how open, flexible and extensible the OpsRamp Platform is.”
OpsRamp provides integrations with tools across the modern IT ecosystem, including the following:
- Applications/Application Servers: Dell, Hitachi, IBM, Microsoft, Nginx
- Databases: Apache Cassandra, CockroachDB, Couchbase, IBM DB2, Microsoft SQL Server
- Networks: Aruba, Brocade, Cisco, HPE, Intel, Juniper
- Operating Systems: CentOS, Linux, Microsoft Windows, Red Hat
- Virtualization: Cisco, Microsoft Hyper-V, Nutanix, VMware
- Public Cloud: Amazon Web Services, Google Cloud Platform, Microsoft Azure, Alibaba
- Storage: Dell, EMC, Hitachi, NetApp, Pure Storage
- ITSM: Atlassian, Autotask, BMC, Freshservice, ServiceNow, Zendesk
- SSO: Azure Active Directory, Centrify, Okta, OneLogin, PingIdentity
- Monitoring/3rd Party Events: AppDynamics, Datadog, Dynatrace, New Relic, Prometheus, Splunk
For integrations not yet supported out-of-the-box, OpsRamp customers and partners can easily build custom integrations between OpsRamp and any tool that supports REST APIs. OpsRamp’s API developer experience supports the OpenAPI specification, an industry-standard language-agnostic interface for describing and documenting RESTful APIs. Inbound authentication between OpsRamp and integrated tools is handled by OAUTH2 and/or Webhooks.
OpsRamp’s ever-growing integration ecosystem provides IT and service delivery teams with the hybrid visibility, control and service-centric AIOps they need to manage the real-time health and performance of their digital services.
The Latest
AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...
Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...
Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...
When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...
In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...
Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...
AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...
Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...
For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...
Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...