4 Steps to Reduce Risks and Costs of Open Source Languages
May 29, 2019

Bart Copeland
ActiveState

It's become common practice to use open source languages to code, helping companies iterate and release more quickly in a DevOps world. However, these languages bring some challenges with them, adding complexity and risk. Developers are still wasting time on retrofitting languages to comply with enterprise criteria, according to ActiveState's annual developer survey.

The amount of time spent on programming has dropped almost 20% since last year. More than 61% of respondents spend just four hours or less per day programming — that is, actually doing their job. Developers aren't able to focus efforts on high-value work due to non-coding activities like retrofitting software for security and open source licenses after application software and languages have been built.


Another important finding is that 41% of enterprise IT departments experienced some or many problems ensuring that security is up to date with the latest or most secure version of every package. In addition, 40% experienced some or many problems building new, stable releases that behave the same as old releases.

These statistics speak to the fact that IT departments lack visibility into new security threats and struggle to track code in production for required updates, patches and new vulnerabilities. Development grabs from open source ecosystems, which consist of thousands of third-party packages that may or may not comply with enterprise security and open source license criteria. This, of course, can expose a company to application-level security vulnerabilities.

As for open source languages themselves, popularity and satisfaction aren't always connected. For daily use, developers most often use SQL (80%) — but Python has the highest satisfaction levels: 77% were satisfied or very satisfied with it.

Perhaps its satisfaction is owed to the fact that Python is quite flexible. It began as a scripting solution for sysadmins, then became useful to web development for programmers and is now the driving force behind machine learning. The language's usage continues to grow — developers clearly want to use it. So, to support this usage, organizations need to ensure their developers can do so safely and securely.

And for organizations to effectively decrease the risks and costs of managing open source languages they should implement a systematic and automated workflow: Open Source Language Automation. This workflow can be broken down into four steps:

1. Define Policies

Companies must set organization-wide open source language policies, version controls and triggers.

2. Centralize Dependencies

Track languages and packages across DevOps cycles to assess open source usage and ultimately produce a single source of truth for open source languages.

3. Automate Your Builds

Reduce vulnerabilities and increase application quality by automatically creating builds with a systematic, repeatable build process organization-wide.

4. Deploy and Manage Artifacts

Automatically update all test, stage and production servers with the appropriate and latest open source language builds.

Open source languages provide the flexibility developers are looking for, so they are here to stay in the enterprise. Using the four steps will help your organization continue to iterate quickly, but with greater efficiency and security.

Methodology: ActiveState surveyed 1,250 developers in 88 countries on what they're spending their work hours on and how they are using open source languages. Respondent ages ranged from under 25 to 61+ years, with those in their early 40s making up the largest group at almost 15%. The largest number of responses came from the U.S., Canada and Germany.

Bart Copeland is CEO and President of ActiveState
Share this

Industry News

January 14, 2021

Oracle is making its popular APEX low-code development platform available as a managed cloud service that developers can use to build data-driven enterprise applications quickly and easily.

January 14, 2021

Parasoft announced its C/C++test update to support IAR Systems' build tools for Linux for Arm.

January 14, 2021

Harness raised $115 million in financing, reaching a valuation of $1.7 billion in just three years after launching from stealth.

January 13, 2021

Slim.ai launched with its cloud-based DevOps automation platform built specifically for software developers.

January 13, 2021

WhiteSource announced new WhiteSource Advise support for JetBrains' PyCharm and WebStorm integrated development environments (IDEs).

January 12, 2021

Red Hat has added new features to Red Hat Runtimes.

January 11, 2021

KubeSphere announced its expanded relationship with AWS to offer KubeSphere as an AWS Quick Start.

January 07, 2021

Red Hat announced its intent to acquire StackRox

January 07, 2021

Cigniti Technologies announced a partnership with Sonatype to help enterprise customers innovate faster and easily mitigate security risk inherent in open source.

January 07, 2021

Lacework announced a $525 million growth round with a valuation of over $1 billion.

January 06, 2021

BMC announced several new capabilities and enhancements for the BMC Automated Mainframe Intelligence (AMI) and Compuware portfolios that enable BMC mainframe customers to protect uptime and availability, defend the mainframe against cybersecurity threats, and advance enterprise DevOps.

January 06, 2021

Sysdig has achieved Service Organization Control (SOC) 2 Type II compliance for the Sysdig Secure DevOps Platform.

January 05, 2021

Allegro AI announced a rebranding of its key product Allegro Trains as ClearML.

January 05, 2021

Acryl unveiled a pilot service for Jonathan, an integrated AI platform that can be used in a variety of industries with a spectrum of users from non-experts to professional developers.

January 05, 2021

Weaveworks announced a $36.65 million Series C funding round.