What is Network Analytics and why should you care ?

Despite the many innovations and numerous promises made by SDN (Software Defined Networking), today’s networks are still incredibly complex and very difficult to manage. The rise of IoT devices and M2M communication has further complicated the already dense network. Network operators are finding it increasingly difficult to gather, and more importantly, make sense of the vast information from the various network elements. Due to the lack of critical insights, companies have a hard time to assure their compliance with various company and government policies.  Network Analytics, therefore, becomes necessary to address such network and business concerns.

Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.

 Geoffrey Moore

What is Network Analytics?

Network Analytics provides the network operators and administrators with a deeper understanding of their network. A typical network – enterprise, data center, telecom or cloud –  is hugely diverse. It comprises various devices from multiple vendors – a load balancer from F5, a firewall from Checkpoint, routers, and switches from Cisco and Juniper. Pinpointing and addressing any issue in such a network without relevant statistics and analytical information is tedious and error-prone.

Network analytics allows the operator to collect valuable continuous data, analyze trends and predict future behavior.  True network analytics needs to start by being completely vendor agnostic. It should be able to collect data across disparate devices, store the relevant time series data and correlate that data in real time.

Why is Network Analytics Important?

Network Analytics gives a deep insight into the IT network and helps the administrators make smart and informed business decisions.

It can be particularly useful in preventing, detecting and responding to security threats. The complexity of IT networks has ushered a wide range of cybersecurity attacks. Yahoo recently admitted to a data breach of around 3 billion users. Traditional security measures are no longer enough to prevent such threats. Network Analytics play a key role in detecting any anomalies in the network and predicting and alerting the administrator to prevent or respond to security breaches.

Telecom and Datacenter network administrators are leveraging network analytics to optimize their infrastructure. Administrators are more equipped – with deep understandings and meaningful insights – to plan capacity and dimension their complex networks.

Network Analytics can aid and transform many industry verticals. It can play a crucial role in increasing network efficiency and reducing operational expenditure. It has found a wide range of use cases in security, capacity planning and optimization, service assurance, and many more.

Benefits of Network Analytics

1. Learns the current health of the network through real-time statistics
2. Predicts potential service disruptions before they occur
3. Monitors and manages the compliance and assurance process
4. Improves network reliability and guarantees network performance as per SLAs

Realizing Analytics and Machine learning with Anuta ATOM

Anuta ATOM platform runs advanced analytics, modern machine learning frameworks, and YANG data models to create a smart network powered with complete closed-loop automation.

It collects operational & performance data from every network element using a variety of data sources. ATOM supports the highly efficient streaming telemetry data where the network devices push incremental updates to ATOM. Streaming telemetry is a modern model-driven approach where the data is described using YANG and streamed over TCP, UDP or gRPC. ATOM also supports legacy data sources such as SNMP, SNMP Trap and Syslogs.

Features and benefits of Anuta ATOM

1. Offers Multi-domain and Multi-Vendor support – Collects data from 1M+ devices across 45+ vendors.
2. Supports streaming telemetry with data interval in milliseconds.
3. Provides advanced customizable visualization and deep insights using Grafana and Time series database.
4. Built using a web-scalable microservices architecture that facilitates high availability
5. Empowers smart networking through orchestration, automation and policy control
6. Offers SDKs and open APIs to integrate with external applications easily

Example of Network Analytics in Action

Let’s take a look at how the Anuta ATOM can very efficiently detect and prevent data theft. ATOM continuously monitors and collects information from all network elements. It reads and analyses data to learn the bandwidth utilization trends during busy and non-busy hours. A data theft activity results in a spike of bandwidth in the devices. ATOM using its advanced analytics platform detects this anomaly, reports and alerts the network administrator and waits for approval to take corrective actions. After obtaining the necessary approvals from all the stakeholders, Anuta ATOM automatically sets new rules on firewalls to block the offending user and prevents data theft.