Any, even not very large store can become a victim of an attack. Competitors or pranksters can “put down” the site with multiple requests, launch bots, or fill the database with fake registrations. Special protective measures are needed.
You can use AntiDDoS protection; the provider can provide it; if not, you need to connect a separate solution. You can also use complex systems for filtering application traffic, such as WAF, Web Application Firewall – a protective screen designed for web applications and websites. Here’s what he can do:
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When many requests are automatically sent to the site, the security tool will not let them through, and the site will work usually.
Technical Traffic Analysis
The tool automatically looks at users’ traffic coming to the server and analyzes whether a natural person or a bot is accessing the online store. This is determined by several indicators: behavior, network time, operating system, etc. After identifying the bot, you can immediately cut it off, and it will not get to your site.
It prevents competitors from collecting and copying all of your products, prices, and photos to host them.
Protection Against The Selection Of Logins And Passwords
It prevents attackers from gaining access to your customer accounts. For example, to steal bonus points or their data.
Search For Vulnerabilities
Constant monitoring of the site for vulnerabilities in the code that attackers can exploit
The system notifies you about them to protect the site before the attack. If you use cloud hosting, WAF can be connected to the provider.
We Use Connect Monitoring To Monitor The Operation Of The Infrastructure And The Online Store
You need to monitor both the infrastructure on which the online store operates and the operation of its services themselves. Monitoring allows you to collect work metrics and respond to incidents in time: prevent or quickly eliminate them.
If you are deploying a store on cloud servers, you can use different tools for monitoring, such as the ELK stack. These are three Open Source tools: Elasticsearch, Logstash and Kibana; they are used to analyze, collect and store metrics. Suppose you configure data collection and the application itself to send data to ELK. In that case, you can understand which failures on which servers lead to losses in the online store since ELK visually displays the relationship of events in different subsystems.
You can also connect a ready-made monitoring service from the provider. It ties in one click and helps collect the necessary data about the system, including any user parameters.