DevOps for Data
DevOps is one of the hottest trends in the software industry and successful DevOps implementation is the goal of most progressive IT organizations (see chart below, courtesy of Google Trends). DevOps (short for development and operations) is a set of automated software practices that combine software development (Dev), testing and IT operations (Ops) to shorten the software development life cycle while delivering features, fixes, and updates frequently in alignment with the business’ objectives.
DevOps is typically cross-functional (people from different IT-related business units) and uses different software tools. These tools usually fit into one or more of the following categories:
- Coding – code development and review, source code management tools, code merging
- Building – continuous integration tools (like Jenkins), build status
- Testing – continuous testing tools (like QuerySurge, Selenium, Cucumber, JMeter) that provide feedback on business risks
- Packaging – artifact repository, application pre-deployment staging
- Releasing – change management, release approvals, release automation
- Configuring – infrastructure configuration and management, infrastructure as code tools
- Monitoring – applications performance monitoring, end-user experience
While we’re at it, let’s add a few more terms to the DevOps movement:
Continuous Integration (CI). Continuous Integration is about automating build and test processes to make sure the resulting software is in a good state, ideally every time a developer changes code. CI helps development teams avoid integration issues where the software works on individual developers’ machines, but it fails when all developers combine their code.
Continuous Delivery (CD). Continuous Delivery goes one step further to automate a software release, which typically involves packaging the software for deployment in a production-like environment. The goal of CD is to make sure the software is always ready to go to production, even if the team decides not to do it for business reasons.
Continuous Deployment (also CD). Continuous deployment goes one step further than continuous delivery. With this practice, every change that passes all stages of your production pipeline is released to your customers. There’s no human intervention, and only a failed test will prevent a new change to be deployed to production.
Continuous Testing. One of the hottest buzz terms in the testing world, continuous testing is the process of executing automated tests as part of the delivery pipeline to obtain immediate feedback on the business risks associated with a release candidate. Continuous testing cannot be implemented without test automation.
DevOps principles demand strong interdepartmental communication and rely heavily on automation tools.
There are 6 primary goals of DevOps:
- Increase speed of development and release processes
- Make builds more reliable
- Shorter turnaround for new features and bug fixes
- Greater Scalability of applications and infrastructure
- Increased security by automating compliance practices
- Improved collaboration throughout the development lifecycle
And now the movement to incorporate a DevOps-type of automated process for data has grown stronger. These practices are often referred to as DevOps for Data or DataOps and apply DevOps tools and techniques to data. Data is growing geometrically and applying automation to develop, deploy and validate/test the data is becoming more critical, as businesses are implementing BI & Analytics to make sense of their data and to leverage it in hopes of providing a competitive advantage.
SonicWall firewall logs auditing and monitoring
The network of a company has to be protected from threats and attacks by firewalls. They aid in traffic management, track and document unwanted access, and prevent harmful traffic from entering the network. You may take use of the actionable insights provided by the syslog data created by firewalls to reduce potential network dangers.
Together with other firewall devices, EventLog Analyzer offers out-of-the-box support for SonicWall firewalls. It manages, analyses, and monitors all firewall log data, greatly simplifying the auditing process. Auditing SonicWall firewalls with EventLog Analyzer has other advantages, such as:
- A user-friendly interface with an intuitive dashboard.
- Over 60 out-of-the-box reports for SonicWall firewalls that aid in security and compliance auditing.
- Easily customizable report templates to meet internal policy needs.
- Custom compliance reports to help you comply with regulations like the GDPR.
- Real-time email and SMS alerts on configuration changes and events of interest.
- Powerful log forensic analysis with a high-speed log search engine that uses various search algorithms, including Boolean, range, wild card, group searches, and more.
EventLog Analyzer helps monitor SonicWall audit logs and provides simple, predefined audit reports with in-depth information about SonicWall devices. These reports are also presented as intuitive graphs and charts for improved data visualization.
EventLog Analyzer’s SonicWall reports fall under the following categories:
These reports give insights into security threats such as SYN flood and routing table attacks, connections that have been denied, and details on critical attacks. These security insights help prevent or mitigate potential attacks on the network.
Security policies and rules monitoring
These reports track changes made to firewall rules and network policies, which can help with periodic policy cleanup. They also help monitor all access points, security events based on severity (emergency, alert, error, and warning events), and system events (clock updates, removed and inserted PC cards, and status of log space).
You can get instant notifications for any critical event via SMS or email by configuring predefined alert profiles, or build custom alert profiles by defining criteria that fit your needs. Log data is automatically archived for forensic analysis, helping your organization meet regulatory compliance standards. Archiving log data lets administrators investigate past data by drilling out raw or formatted log data anytime they like.