MEF17: LSO APIs, SD-WANs and automation

I attended last week’s MEF17 conference in Orlando, where the telecom industry association announced its MEF 3.0 Transformational Global Services Frameworkfor defining, delivering, and certifying agile, assured, and orchestrated communication services across a global ecosystem of automated networks”. MEF members have been busy defining a set of APIs for Lifecycle Services Orchestration(LSO), with a strong focus on inter-carrier orchestration for delivering end-to-end services across multiple domains and these were discussed in many conference sessions and demonstrated by vendors and service providers in the Proof of Concept Showcase.

It was no surprise to hear everyone talking about delivering SD-WAN and other virtualized services, but because these are largely software-driven constructs, it’s critical that the industry adopt open standards in order to support multi-vendor, multi-carrier deployments. This is where the MEF plans to take a leading role, using its base of standards for inter-carrier Ethernet services as a springboard. Here’s a link to the MEF 3.0 video that describes the association’s global services framework, which encompasses not only service definitions and APIs but also an automated, self-service certification platform and a broad community of vendors, service providers, open source projects and other standards bodies.

Automation was the other hot topic at the event. In his keynote, MEF CTO Pascal Menezes stressed the importance of telemetry-driven analytics and machine learning (“AI analytics”) for automating service orchestration at the connectivity layer and for virtualized, overlay services. He also talked about using visibility and analytics to make networks application aware for intent-based service orchestration.

I am keen to track the MEF’s progress in 2018 as it works to define APIs that facilitate automation at both the service and network layers and I’m hoping we’ll see tangible results in this area prior to next year’s MEF18 event.


Four key building blocks for insight-driven network automation

The migration of content, applications and services to the cloud is driving network  behaviors characterized by constantly shifting traffic flows, complex end-to-end paths and unpredictable bandwidth demand. Small, agile DevOps teams are engaged in cloud-native application and service deployments that are highly dynamic, distributed and diverse. These trends are creating serious operational challenges for both cloud-native webscalers and network service providers (NSPs), which are exacerbated by the dramatic expansion of the potential attack surface beyond the traditional security perimeter. In addition, a proliferation of weakly secured IoT devices has created a platform that hackers are exploiting to launch massive scale botnet-based DDoS attacks.

My colleague Tim Doiron and I just published an ACG Research white paper on “Powering Intelligent Network Services With Real-Time Visibility, Analytics and Automation” that describes how NSPs and webscalers can use real-time visibility, analytics and automation to overcome these challenges by taking advantage of the latest advances in network infrastructure hardware and software. The paper examines the four key building blocks that enable operators to realize the benefits of real-time, insight-driven network automation:

The data plane should be fully instrumented in both hardware and software, capable of extracting visibility data used for tracking, identifying and characterizing traffic flows. Data plane fabrics based on custom ASICs will continue to play a vital role by providing embedded support for packet flow classification mechanisms, flexible packet header and payload pattern matching for filtering functions, built-in flow replication and the ability to support millions of granular ACL rules.

The control plane should be fully programmable and evolve to incorporate a sophisticated orchestration layer implementing multiple applications for real-time network automation use cases in response to detected failures, anomalies, performance bottlenecks, sub-optimal utilization and security threats.

Multi-domain, multi-layer visibility is critical for dynamic traffic flows traversing complex end-to-end paths while the underlying network topology shifts in response to changing conditions. Another critical visibility requirement is identifying servers and end points not just by IP address, but by application, service or subscriber, which is a non-trivial problem in today’s vast and complex Internet. NSPs and webscalers also need a map of the “supply chain of the Internet”, which tracks the relationships and dependencies between cloud-native applications and services, CDNs and peering and transit networks.

Big Data analytics plays the critical role of extracting actionable insights in real-time by ingesting petabytes of data, including streaming telemetry for visibility into network paths, traffic flows and performance, but also data collected from a wide array of other sources that provides visibility into the identity of applications, services and subscribers.

In combination, these four key building blocks enable operators to deploy intelligent networks that use visibility and analytics to drive closed-loop feedback for insight-driven network automation:

To learn more, read the white paper and tune into the upcoming Light Reading webinar “Real-Time Visibility & Analytics to Enable Actionable Intelligence & Network Automation“, to be held Thursday, November 9, 2017, 12:00 p.m. New York / 6:00 p.m. London.



Automation-centric monitoring for cloud-scale infrastructure

I just published an ACG Research market impact report on the Juniper Networks’ AppFormix monitoring and automation solution for intent-driven cloud-scale infrastructure. The report examines the ramifications for data center operators of the highly dynamic, cloud-scale application deployment environments I described in the “3 D’s” of hybrid and multi-cloud application deployment.

Data center operators have access to a wealth of tools for application, infrastructure and network monitoring, provided by numerous vendors and open source initiatives. Yet the current generation of tools fall short in helping operators overcome the challenges of managing cloud-scale application deployment, which is characterized by massive scale, software-driven complexity and highly dynamic run-time environments in which workloads and resources fluctuate constantly. These operators need real-time, full stack monitoring that spans the entire environment:

They also need tools that can remove time-consuming manual workflows from the remedial action feedback loop. Infrastructure monitoring and analytics should feed actionable insights directly to the orchestration layer to automate the process of taking action in response to anomalies or changing conditions by reallocating resources or redistributing workloads. In other words, infrastructure monitoring needs to move from operator-centric to automation-centric.

Collecting and analyzing full stack monitoring data in real time is a Big Data problem, but Juniper Networks’ AppFormix takes an innovative approach to solving this problem that utilizes the distributed computing resources inherent in cloud-scale infrastructure to perform local machine learning on the metrics extracted from each node, significantly reducing the flow of data streamed to the central analytics engine and database.

Providers of infrastructure monitoring solution are busy incorporating machine learning and Big Data analytics into their products. However, in addition to its unique approach to Big Data analytics, what differentiates the Juniper Networks’ AppFormix solution is the integration of analytics-driven, policy-based control that continuously monitors key metrics against pre-defined SLAs and automatically triggers the orchestration layer to make the adjustments necessary to assure the operator’s business objectives.  The net result is automation-centric monitoring for intent-driven cloud-scale infrastructure.

For more information, watch the ACG Research Hot Seat video with Sumeet Singh, AppFormix founder and VP engineering, Juniper Networks.