Mike Fratto is a senior research analyst at S&P Global Market Intelligence, leading the observability and networking research segments. He focuses on understanding the competitive landscape of the segments he covers by understanding the competitors’ strategies and putting them into context. He has extensive experience in enterprise security and network infrastructure products, as well as consulting with enterprise IT, equipment and software vendors, and service providers. Mike’s current interests in observability include the ways that metrics, events, logs and trace (MELT) data is analyzed and presented to the user via contextual visualizations; how MELT data is used to create and maintain dynamic application and infrastructure topologies; the application of artificial intelligence and machine learning to surface new insights; and observability’s role in optimizing manual and automated workflows and processes. Mike is interested in network automation in all its forms, including software-defined networking, scripting and automation systems. Networking in support of cloud and microservices continues to be an important, vibrant and competitive field. Mike graduated from Syracuse University with a bachelor's degree in information science and technology.
The company continues to enhance its eponymous product with streamlined workflows throughout the entire troubleshooting and resolution process with its AI Investigator, Service Explorer and Observe for Snowflake offerings. The addition of Open Telemetry-Native APM for application performance monitoring extends Observe's visibility into the application layer.
Enterprises are increasingly investing in networking for AI; InfiniBand is not over yet, but Ethernet looks likely to have a role in AI networking. Networking vendors are taking divergent paths to support AI workloads, but they are starting to converge on a set of standards and best practices.
Software-defined networking continues to represent an active transition for enterprises in the datacenter and campus. The operational benefits from automating network management using a model-based framework is a primary driver and is preparing network IT for advanced automation use cases due to the growth in cloud services and cloud-native application architectures.
Software-defined networking continues to represent an active transition for enterprises in the datacenter and campus. The operational benefits from automating network management using a model-based framework is a primary driver and is preparing network IT for advanced automation use cases due to the growth in cloud services and cloud-native application architectures.
NMS deployments are increasingly shifting to cloud-based deployments, which relieves operational burden on enterprise IT staff, allowing them to focus on management and operations. Enterprises want to improve efficiency and reduce the time spent on manual tasks and shifting staff talent to value-added capabilities in design and architecture. Increasingly, they will need to include cloud networking for monitoring and operating virtual network elements from a single management plane.
NMS deployments are increasingly shifting to cloud-based deployments, which relieves operational burden on enterprise IT staff, allowing them to focus on management and operations. Enterprises want to improve efficiency and reduce the time spent on manual tasks and shifting staff talent to value-added capabilities in design and architecture. Increasingly, they will need to include cloud networking for monitoring and operating virtual network elements from a single management plane.
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