Microservices Rising, Legacy Security Falling Short
August 15, 2016

Amir Sharif
Aporeto

The software industry has accelerated its shift towards microservices and has fully embraced distributed, cloud native apps. Because existing application security models were designed for a different era, they are woefully inadequate, exposing both consumers and companies. By (mis)matching where software is going with what application security has been, and as evidenced by several recent high-profile leaks, we are all at risk.

Finding their roots in the 90s, “microservices are a more concrete and modern interpretation of service-oriented architectures used to build distributed software systems.” The 90s marked the dawn of the distributed application era as it exists today. Precisely and not surprisingly, it was also the time that defined data center security with the ubiquitous use of firewalls, ACLs, NAT, etc.

Given distributed applications’ history and coexistence with erstwhile proven security methods, the central question is what has changed to render these applications less secure? The answer is feature velocity, application scalability, and shifting topology.

Microservices and DevOps have enabled companies to be faster and more agile, delivering more features in less time. One of the “features” of cloud-native applications is scalability. Take the latest app craze, Pokemon Go, and notice its download patterns from a single mirror site.


There was a 6X download demand increase from May to June and a commensurate drop in July. As the game grew (and apparently shrank) in a short time, it put tremendous stress on the underlying infrastructure because of its constantly changing topology.


Before the cloud and the elasticity of its underlying infrastructure, and before microservices and the current-day distributed applications, change was infrequent, planned for, and required proactive provisioning. Accordingly, resource usage – or rather "reservations" – were predictable and resembled a step function (see “Your Father’s Oldsmobile” in the chart above). In contrast, distributed apps like Pokemon Go have unpredictable user demand curves and seem more like a random function. As the elastic infrastructure responds to the distributed application’s need for scale by provisioning more computation, storage, and network resources, the application topology changes. These rapid changes are disproportionately (quadratically) difficult to respond to when network communications are central to application security, making this precisely a mismatch between distributed application needs and existing security methods.

Existing security methods were designed when Your Father’s Oldsmobile was in vogue and change was more predictable and less frequent. Change request submissions tickets were issued to someone, approved manually, and rolled into production slowly. A bevvy of automation tools and startups are attempting to solve this problem through automation and machine learning; however, there are real technological and operational limitations that inhibit scaling. In the process, the application and, by extension, the user is left exposed to real security vulnerabilities.

Distributed applications require distributed security and a departure from the old-fashioned world of perimeter-based or network-enforced design models.

Amir Sharif is Co-Founder of Aporeto.

Share this

Industry News

April 25, 2024

JFrog announced a new machine learning (ML) lifecycle integration between JFrog Artifactory and MLflow, an open source software platform originally developed by Databricks.

April 25, 2024

Copado announced the general availability of Test Copilot, the AI-powered test creation assistant.

April 25, 2024

SmartBear has added no-code test automation powered by GenAI to its Zephyr Scale, the solution that delivers scalable, performant test management inside Jira.

April 24, 2024

Opsera announced that two new patents have been issued for its Unified DevOps Platform, now totaling nine patents issued for the cloud-native DevOps Platform.

April 23, 2024

mabl announced the addition of mobile application testing to its platform.

April 23, 2024

Spectro Cloud announced the achievement of a new Amazon Web Services (AWS) Competency designation.

April 22, 2024

GitLab announced the general availability of GitLab Duo Chat.

April 18, 2024

SmartBear announced a new version of its API design and documentation tool, SwaggerHub, integrating Stoplight’s API open source tools.

April 18, 2024

Red Hat announced updates to Red Hat Trusted Software Supply Chain.

April 18, 2024

Tricentis announced the latest update to the company’s AI offerings with the launch of Tricentis Copilot, a suite of solutions leveraging generative AI to enhance productivity throughout the entire testing lifecycle.

April 17, 2024

CIQ launched fully supported, upstream stable kernels for Rocky Linux via the CIQ Enterprise Linux Platform, providing enhanced performance, hardware compatibility and security.

April 17, 2024

Redgate launched an enterprise version of its database monitoring tool, providing a range of new features to address the challenges of scale and complexity faced by larger organizations.

April 17, 2024

Snyk announced the expansion of its current partnership with Google Cloud to advance secure code generated by Google Cloud’s generative-AI-powered collaborator service, Gemini Code Assist.

April 16, 2024

Kong announced the commercial availability of Kong Konnect Dedicated Cloud Gateways on Amazon Web Services (AWS).

April 16, 2024

Pegasystems announced the general availability of Pega Infinity ’24.1™.