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Extract, Transform, and Load (ETL) is a crucial process in data warehousing, where data is extracted from multiple sources, transformed to fit the target schema, and then loaded into a data warehouse. ETL testing is a critical step in ensuring the quality and accuracy of the data loaded into a specific location.
ETL testing is a complex and challenging task that requires a deep understanding of data and the ETL process. In this article, we will discuss some of the best practices for ETL testing that can help you improve the quality of your data and minimize errors during the ETL process. ETL testing can be helpful for sectors that handle a lot of data, frequently from different sources.1- Automate your testing
Automation in testing is essential to ETL testing best practices. Automating your ETL testing processes helps you save time, reduce errors, and increase efficiency. You can use ETL testing tools to automate repetitive testing tasks and generate detailed reports.2- Understand the data
To perform ETL testing effectively, it’s crucial to thoroughly understand the data being processed, including its
This knowledge will help you identify potential issues and anomalies in the data, ensuring that the final output meets the business requirements.3- Plan your testing strategy
Develop a comprehensive ETL testing plan that covers all aspects of the ETL process, including data extraction, transformation, and loading. This plan should define the testing scope, methodology, expected outcomes, and tools &resources required to execute the plan.
An example of a testing strategy could be in the following order:
Data Extraction Testing: Verify that the data is being extracted from the correct source system
Data Transformation Testing: Verify that data is being transformed correctly and consistently
Data Loading Testing: Verify that the data is loaded into the correct target system
Data Reconciliation Testing: Compare the data in the source system to the data in the target system to ensure that the data has been accurately transformed and loaded
Regression Testing: Conduct regression testing to ensure that changes to the ETL process do not impact existing functionality. Verify that the ETL process works correctly after system upgrades or changes.
Performance Testing: Test the performance of the ETL process for both small and large data sets. Verify that the ETL process performs within acceptable time and resource constraints. Investigate and resolve any performance issues.
Error Handling Testing: Test error handling for different scenarios, such as invalid data, network failures, and system errors
Security Testing: Test the security of the ETL process, including data encryption, authentication, and access controls. Verify that the ETL process complies with regulatory and security requirements.4- Use test data wisely
The quality of your test data is critical to the success of your ETL testing efforts. Use representative data sets that simulate real-world scenarios and edge cases and cover various data types and formats.
Real-world scenario data:
Patient demographic data, such as: name, age, gender, and contact information
Medical history data, such as: diagnoses, medications, procedures, and allergies
Claims data, such as: billing codes, dates of service, and insurance information
Provider data, such as: physician names, practice locations, and credentials
Edge case data:
Patients with unusual or rare medical conditions that require special handling
Patients with multiple or overlapping medical conditions that require complex data transformations
Claims with incorrect or incomplete billing codes
Invalid or missing patient and provider information5-Verify data integrity
As part of your ETL testing efforts, you should verify the integrity of the data being processed. This includes checking for data accuracy, completeness, consistency, and conformity to data standards and rules.
Here are two ways to verify data integrity for ETL testing:
Data profiling: Profiling the data before and after the ETL process can help you identify data quality issues, such as missing or duplicate data, and validate the accuracy of the data. Data profiling tools can help you compare source data to target data, identify patterns and anomalies, and highlight discrepancies.
Data reconciliation: Comparing the data in the source system to the data in the target system is an effective way to verify data integrity. You can identify missing, duplicated, or inconsistent data by comparing the source and target systems data. You can also use data reconciliation tools to automate this process and generate reports highlighting discrepancies.
The ETL process transforms data from its source to the target format. It’s essential to validate these transformations to ensure the data is transformed correctly and consistently. You can use two crucial aspects of software testing to complement ETL testing and strengthen the ETL process:
Unit testing: This testing is typically done using mock data and test cases that cover various data scenarios. By testing each transformation individually, you can identify and fix any issues early in the ETL process.
Integration testing: Integration testing involves testing the entire ETL process to ensure that the data is transformed accurately and consistently. This testing typically uses real-world data and test cases covering various data scenarios. You can identify and fix data transformations and flow issues by testing the ETL process.
Check our article “Integration Testing vs Unit Testing” to understand the difference between the two practices7-)Test data loading
The final step in the ETL process is to load the data into the target system. It’s essential to test the data loading process to ensure that the data is loaded correctly and that there are no data loss or corruption issues.
If you have further questions about ETL testing, reach out to us
He received his bachelor’s degree in Political Science and Public Administration from Bilkent University and he received his master’s degree in International Politics from KU Leuven .
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Creating a consistent style, planning content, and knowing when to post is key. Follow more of these Instagram best practices and grow your account in 2023.
It seems like things never stop changing on Instagram. The network keeps adapting its features to compete in the increasingly crowded social media landscape. So, do the Instagram best practices that worked in 2023 still apply in 2023?
While the fundamentals of your Instagram marketing strategy should stay consistent, some of the tactics you need to achieve your goals are shifting. Keep reading for a list of best practices that will help you succeed on the platform in 2023 and beyond.
Bonus: 14 Time-Saving Hacks for Instagram Power Users. Get the list of secret shortcuts Hootsuite’s own social media team uses to create thumb-stopping content.25 Instagram best practices for 2023
Instagram marketing best practices1. Set clear goals
You’ve heard this from us before and you’ll hear it again. Every great social media marketing strategy begins with a solid set of clear, measurable goals.
Are you planning to use Instagram to build brand awareness? Drive product sales? Engage with your community? Maybe all of the above?
What you want to get out of Instagram will determine what you should put into it. Think about how the platform’s various surfaces – feed posts, Reels, Stories – can contribute to real business goals.2. Post at the right time
Hootsuite research shows that the best time to post photos on Instagram is 11 a.m. on Wednesdays. For Reels, it’s 9 a.m. and 12 p.m. Monday to Thursday. Keep in mind that the average Instagram business account posts 1.71 main feed posts per day.
That’s a good place for you to start. But to find the most effective time to post for your particular account, you’ll need to understand the Instagram habits of your particular audience.
Hootsuite Analytics provides a heatmap showing when your followers are most likely to be online. It also provides custom suggestions for the best time to post to your followers based on your chosen Instagram goals.
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This allows you to create quality content in dedicated blocks of time, which maximizes your creative resources. It also gives you the breathing room to edit and review your content thoroughly before it goes live.
Hootsuite helps you post consistently with no effort. It allows you to schedule your Instagram posts, Reels, and Stories alongside other social posts, so you can see the complete picture of your social posting schedule in one content calendar.
This also gives you a good overview and allows you to ensure you’ve planned the perfect mix of photos, videos, and carousel posts.4. Engage with your followers
Remember: Instagram is not a broadcasting service. It’s a social network. That means your followers expect two-way communication and a sense of community. If you want people to engage with your Instagram content, you’ve got to get engaged yourself.
Start free 30-day trial5. Tag your products
Nearly half of Instagram users shop the platform weekly.
Brands that tag their products in feed posts see 37% more sales on average. And brands that tag two or more posts per day see a 117% increase in transactions.
Source: Instagram6. Analyze and improve your results
We’ve already mentioned a few times that you’ll need to do some experimentation to learn what works best for your particular audience. That will continue to be an ongoing theme throughout this post.
To learn the results of your experiments, you need to use Instagram analytics. The native Instagram insights tool provides some good information to get you started. To take things up a notch and get a richly detailed picture of your results, it’s a good idea to incorporate professional analytics tools like Hootsuite.
The Instagram analytics within Hootsuite include downloadable and exportable charts and graphs that make it easy to understand what’s working and what’s not. You can also see how your Instagram efforts compare to those on other social media platforms.
One particularly useful tool in Hootsuite Analytics is the ability to compare the performance of Instagram Reels to TikToks. This can help you refine your short video strategy – not just within Instagram, but across platforms.
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Instagram Reels best practices7. Make (more) Reels
Not using Reels yet? It’s definitely time to start.
Instagram is leaning hard into video in general and Reels in particular. Reels already account for 20% of time spent on the platform. And Hootsuite research shows that Reels get up to 300% more engagement than regular Instagram videos. The Instagram algorithm loves Reels, too.
So, this is a simple but very important Instagram best practice. Just make (more) Reels.8. Show your human side 9. Make the most of the first 3 seconds
Capture attention right upfront with dynamic motion and teaser titles. (Just make sure you deliver on the promise of your title – watchbait is a big no-no.)
Show (and tell) people in the first three seconds what they’ll get out of your Reel and why they should keep watching. On that note…10. Add text to your Reels
Adding text to your Reels offers a number of benefits. First and foremost, it makes your content accessible to the deaf and hard-of-hearing community. It’s also important for the 20% of Reels views that happen with the sound turned off.
You can also add timed text to emphasize specific points in your video.11. Use trending audio
Incorporating trending audio into your Reels is a great way to boost your exposure. You can identify trending audio by the little arrow next to the name of the sound in any reel.
Tap on the audio to see how many reels have already been made with that sound. Your best chance for getting a boost is using trending audio that doesn’t yet have too many other competing Reels. Aim for 30K or fewer.
In this case, the track already has 285K Reels, so you might want to keep looking for one with less competition.
If you come across audio you love, you can save it for later by tapping the Save audio button. If you specifically want to use it for that trending boost, just be sure to check that it’s still trending when you’re ready to use it.12. Try a template
If you want to use multiple photos and/or video clips in your Reel, a template can be a great way to get started. Using a template automatically syncs your clips to the audio in the original Reel.
Instagram Stories best practices13. Use interactive stickers
Interactive features like the vote button, quiz button, and question button really let you get to know your audience. They also provide a great opportunity for getting your community involved and driving good engagement rates.
Try asking followers what kind of content they want to see from you. Or use the Question sticker to do a follower Q&A.14. Save your best Stories to highlights
Instagram Stories are a great way to experiment with new ideas and more casual content because they disappear after 24 hours.
But sometimes you want your Stories to stick around. For those occasions, there are Stories highlights.
Highlights live on your Instagram page above your grid. In addition to saving your best Stories, you can also use them to create space for extra information about your business or products.
For more ideas, check out our full blog post on how to use Instagram Stories.
Instagram post best practices15. Develop a consistent style
Your Instagram grid should have a visually consistent style, and viewers should be able to recognize one of your posts instantly when it appears in their feed.
One way to achieve this is to keep the colors you use in line with your brand style guide. Another is to use design tools with pre-built templates, like the Canva integration in Hootsuite Composer.16. Use the right hashtags
Social SEO may be reducing the importance of hashtags, but that doesn’t mean you can avoid them altogether.
In particular, using specific niche hashtags can help you connect with existing passionate communities on Instagram. And creating a brand hashtag can help you collect user-generated content and social proof.
Here’s everything you need to know about using hashtags on Instagram:17. Write catchy captions
Yes, it’s the quality of the image that will grab attention and stop the scroll. But you can’t ignore the power of captions on Instagram. Instagram captions help users connect with your brand and learn about what you stand for.
Writing great captions is also one of the best practices for Instagram posts because they help the Instagram algorithm understand what your post is about to help with Instagram SEO. Captions are one of the sources the algorithm checks for relevant keywords when someone searches for content on the platform.18. Use alt text
This is another quick thing you can do to make your content more accessible while also boosting your Instagram SEO ranking signals.
Alt text on Instagram works just like alt text on the web: it provides a text description of what’s in the image or photo.
Instagram uses artificial intelligence to create auto alt text for all posts, but you can customize the alt text yourself for better results.
Check out our detailed instructions for adding alt text to Instagram posts.19. Pin your best posts
The first three spots on your Instagram grid are prime real estate. Fortunately, you can now choose what appears there. You can pin up to three posts (or Reels) to the top row of your grid.
Try pinning your most popular posts, or your most timely. Have a promotion going on? Or a new product about to launch? Pinned posts keep users’ eyes on the prize.
You can also get creative with pinned posts, as Rocky Mountain Soap Company did to tease a new product launch:
Source: @rockymountainsoapco20. Experiment with ad placements
As with your organic strategy, you’ll need to do some testing to see which placements tend to work best for your audience and your goals. The important thing is not to get locked into one format and rely on it to serve your needs. Instagram is constantly changing, so it’s important to keep testing to see if the effectiveness of various formats ebbs and flows with time.21. Partner with creators 22. Unify your product catalog
Here’s how to get your product catalog set up:
The Shopify integration in Hootsuite makes this easy if you already have a Shopify store.
Instagram bio best practices23. Make it complete
You don’t have a ton of real estate in your Instagram bio – just 150 characters to tell users who you are and why they should stick around.
But you can bulk this up by completing all the fields available on your Instagram profile – like your profile picture, address, a link, and an account category. On that note…24. Choose the right account category
Using the correct category in your Instagram bio makes it easier for people to find you and understand what your brand is all about.
It’s also an important feature for enhanced tagging. If you collaborate with other brands or creators, enhanced tagging shows each account’s contribution to a post, including the account category.
Source: Instagram25. Get verified
To give more credibility to your account, think about getting that blue check and applying for Instagram verification. Instagram verification goes a long way in helping your business account look more professional while preventing impostors from stealing your thunder.
Find out how you can get verified.
For more Instagram bio tips (and even some templates), check out our full post on how to create the perfect Instagram bio. Or, get a quick overview in this video:
Save time managing your Instagram presence using Hootsuite. From a single dashboard, you can schedule and publish posts directly to Instagram (and other social networks), engage the audience and measure your performance. Try it free today.
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Easily create, analyze, and schedule Instagram posts, Stories, and Reels with Hootsuite. Save time and get results.
MLOps is defined as certain practices that ensure the deployment and longevity of ML systems by performing the necessary maintenance for updated versions. Due to its potential benefits MLOps market has grown rapidly: According to Deloitte, the market will be worth $4 billion in 2025, predicting a nearly 12-fold increase in MLOps market size since 2023.
Despite all the benefits ML brings to various business processes, companies are struggling to deploy ML techniques to enhance their efficiency. According to McKinsey, 64% of respondents cannot deploy ML algorithms beyond the pilot stage.
Therefore, we list some of the best practices for implementing MLOps to your business problems.Defining the business problem
A clear business objective is critical to the deployment of successful MLOps. What is your business goal? Increasing production efficiency or profitability, improving sales, etc. With this decision, the company determines the KPI that the ML algorithm should maximize.Promoting team-work
Coming up with successful ML practices is something like making a movie. The stars of the movies are actors but their accomplishment depends on many invisible heroes. The same rule applies to deploying MLOps.
Let’s say your business goal is to increase revenue by 5% without impacting profitability metrics. To achieve this goal, the IT team needs to know the key parameter values that impact revenue. Therefore, they need to communicate with the sales and marketing departments.
The IT team also needs to know the components of fixed and variable costs to protect profitability metrics. Therefore, the finance department must be asked. Otherwise, it would be impossible to write suitable algorithms. Such a task requires teamwork, where the departments can communicate with each other.
However, as a challange to teamwork Deloitte’s study highlights 68% of managers believe that the differences in qualifications between employees are at least moderate. The greater standard deviation of qualifications could mean further difficulties for the communication process. In addition, it means that at least some companies will have to rely on a small portion of their workforce to accomplish a difficult task such as implementing MLOps.Make a cost benefit analysis
Be clear about what features your business needs from MLOps. This approach is the key to the optimal processing of any transaction. Imagine you are a customer who wants to buy a car. You have many options, of course. For example, there are sports cars, SUVs, compact cars and luxury cars. For a cost-optimal purchase, you need to understand which category suits your needs and then compare the different segments and models according to your budget.
The same rule applies when deciding on the optimal MLOps tool for your business. Different MLOps have weaknesses and strengths in accomplishing certain tasks, such as sports cars and SUVs. Therefore, to make a strategic decision, you need to consider several factors, such as your business goals and budget, the MLOps tasks you want to undertake, the format and source of the datasets you want to work with, the capabilities of your team, etc.Validating datasets
The more extensive the data is, the better the reality is represented. Creating a dataset for analysis requires cleaning the data from biases and combining data from different sources (both external and internal).
Batching is another important technique for interpreting data based on changing the frequency basis for a given set of data extractions. In this way, efficient ML training becomes more likely. Also, to ensure data reliability, data pipelines should be automated to control the orchestration of the various data collections. Finally, it is important to consider that development, testing, and production processes may require the use of different data sets.Finding optimal outcome by experimenting
The great British philosopher John Lock viewed the human brain as a white board waiting to be filled with information that is the result of a process of trial and error.
Machines also use a very similar method for learning. Thanks to protocols that guarantee the reproducibility and analysis of the tests or experiments, ML systems gain experience from their mistakes, which eventually lead to better predictive capabilities. The goal of the method is to shorten the life cycle of analysis development and enhance model stability by automating reputations in the workflows of software experts.
Feel free to check our article on experiment tracking for efficient ML experimentation.
Our article about MLOps Tools & Platforms might be helpful for you.
Also, you might want to check our top MLOps platforms list.
We can help you with the search for providers for your MLOps development.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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Product data management, or PDM, is an essential part of any business since it enables:
Smoother supply chain operations
Efficient product development
And an overall higher customer satisfaction level.
However, achieving effective product data management is easier said than done. You can implement a PDM tool, but just throwing money at expensive software will not make all your troubles go away. Effective product data management can be achieved by combining sophisticated software and strategic best practices.
This article explores the top 7 PDM best practices that business leaders must consider to ensure an effective product data management process in their supply chains.1. Conduct product data transcription 2. Understand the business processes that need to be supported
You must understand how your product data is used across the organization if you wish to streamline the flow and management of that data. Understanding company procedures like marketing, sales, customer support, and operations that rely on product data is necessary to do this.
Once you know which business processes need to be supported by the PDM solution, you can determine the product data requirements for each process. This can help you filter out the unnecessary data fields and prioritize the essential ones.3. Define your master data management strategy and structure
Your data model serves as an outline for the structure of the product data. How you will govern your product data moving forward is determined by your master data management plan. This covers details like who will have access to modify the data, how changes will be recorded and audited, and how versioning of the data will be managed.
You can choose from the following data models:
Hierarchical model: In this model, the data has a parent-child-like relationship in which the data is arranged into a tree-like structure. For instance, a sales order has multiple sales items (Child entity) but can only be linked to one sales order (Parent entity).
Relational model: This model involves storing all related data in a single location. For instance, a supplier’s details are stored in one table, with its name, location, contact person, etc.
Entity-relationship (ER) model: This model breaks down your data into different categories to make it more organized. The categories are:
Entities: a product or a customer are separate entities
Relationships: The connections between the entities
Attributes: Something which describes the entity, for instance, product or customer name
Dimensional model: It enables teams to share information across many departments for efficient decision-making and cooperation. This model is mainly used by data warehouses.4. Identify which systems and data need to be integrated 4.1. Data integration
You need to also identify which data will be shared across different systems. After that, you need to automate the data-sharing process by using tools such as RPA to make sure the latest data is available throughout the organization.4.2. System integration
System integration is one of the most important reasons for implementing a PDM tool. You can ensure that your product data is always correct and up-to-date and that all relevant departments have access to it by integrating your PDM system with ERP, PLM, CRM, and eCommerce.5. Create a process for maintaining product data governance
In the current business environment, products and services are frequently changing. These changes are also reflected in their data. Having a proper product data governance mechanism in place can help you efficiently manage these changes. A governance strategy can contain the following systems:
Key roles, including users who are/are not authorized to make changes
How will the changes be made
A process for approving or rejecting changes
A system for tracking and auditing changes.
A good PDM system can help you streamline your product data management process. Most of the software on the market offer system integrations and automated processes to help simplify your product data management process.
Considering these best practices will ensure that your PDM tool and business processes are aligned and work in synergy.
It can also be beneficial to dedicate a team that can regularly update and change the PDM system as the business requirements change.7. Leverage dashboards and reports to track KPIs
Finally, it is important to track the performance of your projects, and product data is an essential element in measuring that. By using dashboards and reports that monitor KPIs on a regular basis, you can identify problems early and take action before they escalate. You can look for a solution that offers built-in dashboards. Some important KPIs for PDM are:
Errors in the dataFurther reading References
Shehmir Javaid is an industry analyst at AIMultiple. He has a background in logistics and supply chain management research and loves learning about innovative technology and sustainability. He completed his MSc in logistics and operations management from Cardiff University UK and Bachelor’s in international business administration From Cardiff Metropolitan University UK.
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Banking chatbots help customers complete transactions with ease using voice or text. Chatbots are useful to banks because they can reduce operational costs, as well as improve customer satisfaction by streamlining interactions.
In this article, we will explain in detail what banking chatbots are, what their benefits are to banks and customers, and how you can build functional banking chatbots.What is a banking chatbot?
Banking chatbot, also called conversational banking (commerce), is the new era of digital service offering. In this era, AI driven virtual financial assistants, perceives and executes the banking transactions of customers. They can also provide opportunities to automate the relationship between the consumer and the bank.
From the historical point of view, digitization of banks began with ATMs and then telephone banking. Evolution process has been followed by online and mobile banking, and now we are in the era of conversational commerce (see Figure 1).
Figure 1: Evolution of digitized banking.
Haptik, a conversational AI firm, developed an intelligent virtual assistant (see Figure 2) to increase customer retention and lessen the load on Tata Mutual Fund’s call centers.
Banking in general and the mutual fund industry have certain distinctions, but they also perform many of the same tasks, such as assisting clients in making the best investment choices. In this regard, Tata’s chatbot answers 90% of customer questions and frees up staff time.
By asking a demo from Haptik, you can see yourself how banking chatbots can help your bank to automate numerous processes.
Figure 2: Intelligent virtual assistant manages customers’ queries.
To learn more about conversational commerce you can read our Top 5 Conversational Commerce Examples & Success Stories article.Why are banking chatbots important now?
Automation provided by chatbots will be beneficial for banks:
Chatbots are cost-efficient. Accenture research shows that 57% of companies agree that chatbots can result in large returns on investment with minimal effort.
Demand for mobile banking is increasing across all age demographics. 24/7 available chatbots integrated to mobile applications can offer users immediate solutions to their urgent problems that they can not resolve via the app.
Customers prefer messaging. Almost all mobile users are familiar with messaging apps such as Whatsapp, Telegram, Slack. Written and conversational communication over those applications is preferred especially by millennials. Banks are also testing using these popular messaging platforms for customer service.Top 4 use cases of banking chatbots 1. Lead generation and qualification 2. Customer service
Salesforce Service Cloud Contact Center is a comprehensive customer service solution that enables organizations to manage their customer support operations and deliver good-quality customer experiences. Intelligent chatbots in the Contact Center provides personalized recommendations to the customers, automates answering customer questions and hands customers to the relevant agent.3. Feedback Collection
Long feedback forms and surveys can be a nuisance to complete. A chatbot can engage customers with its natural language understanding and generation.4. Personalized marketing strategies
Customers’ conversations with chatbots can be analyzed to personalize the bank’s messages for the customer.Top 5 banking chatbot best practices 1. Understand the limitations and challenges of chatbot technology
A good analysis of the capabilities and limitations of existing AI-powered chatbot technology can set the right expectations and goals (see Figure 3).
Figure 3: Optimal chatbot strategy that maximizes customer satisfaction.2. Review how to protect user data
Banking companies are responsible for protecting the information gathered by chatbots. Data security must be reliable for the chatbot. Since data leaks can harm a company’s brand and finances. To enhance your cybersecurity posture, you can read our cybersecurity best practices article.3. Review how to secure transactions
Chatbots, especially those that focus on customer service, increase the attack surface. The transactions that they can complete, authentication procedures etc. need to be reviewed to ensure secure service4. Build specialized chatbots
There are many use cases of banking chatbots from lead generation to customer service. Starting with a domain specific chatbot can simplify requirements which is critical in any technology project.5. Test extensively
There are numerous cases of chatbot failure. Do not let your financial institutions’ conversational agent be a failure. Testing for edge cases can help minimize or prevent screenworthy failures of your company’s chatbot.For more on chabots
For more on chatbots and AI in financial services, feel free to read these articles:
VoiceBots are transforming banking, read more in our comprehensive guide:
You can also download our whitepaper to acquire the most recent guides on conversational AI:
Finally, if you believe your business would benefit from adopting a chatbot platform, we have a data-driven list of vendors prepared. We will help you choose the best one for your business:
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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NGINX is a free, open-source, high-performance HTTP server and a reverse proxy, also known as IMAP/POP3 proxy server. NGINX is famous for its high performance, stability, rich feature set, simple configuration, and low resource consumption. In this article, we will explain about ” Nginx WebServer Best Security Practices”.
sysctl.conf is a simple file containing sysctl values to be read in and set by sysctl. To open sysctl.conf, use the following command –$ sudo vim /etc/sysctl.conf
The sample output should be like this –## chúng tôi - Configuration file for setting system variables # See /etc/sysctl.d/ for additional system variables. # See chúng tôi (5) for information. # #kernel.printk = 3 4 1 3 ##############################################################3 # Functions previously found in netbase # # Turn on Source Address Verification in all interfaces to # prevent some spoofing attacks #net.ipv4.conf.default.rp_filter=1 ..........................................
To prevent a smurf attack, add the following line to sysctl.conf file.net.ipv4.icmp_echo_ignore_broadcasts = 1
To turn on protection for bad icmp error messages, add the following line to sysctl.conf file.net.ipv4.icmp_ignore_bogus_error_responses = 1
To turn on syncookies for SYN flood attack protection,add the following line to sysctl.conf file.net.ipv4.tcp_syncookies = 1
To turn on and log spoofed, source routed, and redirect packets,add the following lines to sysctl.conf file.net.ipv4.conf.all.log_martians = 1 net.ipv4.conf.default.log_martians = 1
To un-source routed packets,add the following line to sysctl.conf file.net.ipv4.conf.all.accept_source_route = 0 net.ipv4.conf.default.accept_source_route = 0
To turn on reverse path filtering,add the following line to sysctl.conf file.net.ipv4.conf.all.rp_filter = 1 net.ipv4.conf.default.rp_filter = 1
To identify alter the routing tables, add the following line to sysctl.conf file.net.ipv4.conf.all.accept_redirects = 0 net.ipv4.conf.default.accept_redirects = 0 net.ipv4.conf.all.secure_redirects = 0 net.ipv4.conf.default.secure_redirects = 0
To turn on execshild, add the following line to sysctl.conf file.kernel.exec-shield = 1 kernel.randomize_va_space = 1
To tune IPv6,add the following lines to sysctl.conf file.net.ipv6.conf.default.router_solicitations = 0 net.ipv6.conf.default.accept_ra_rtr_pref = 0 net.ipv6.conf.default.accept_ra_pinfo = 0 net.ipv6.conf.default.accept_ra_defrtr = 0 net.ipv6.conf.default.autoconf = 0 net.ipv6.conf.default.dad_transmits = 0 net.ipv6.conf.default.max_addresses = 1
To optimize a port, use LBs and add the following line to sysctl.conf file.fs.file-max = 65535
To allow more PIDs, add the following line to sysctl.conf file.kernel.pid_max = 65536
To increase system IP port limits, add the following line to sysctl.conf file.net.ipv4.ip_local_port_range = 2000 65000
To increase TCP max buffer size, set the table by using setsockopt(), and add the following line to sysctl.conf file.net.ipv4.tcp_rmem = 4096 87380 8388608 net.ipv4.tcp_wmem = 4096 87380 8388608
To save and reload the above file, use the below command –# sysctl -p
To turn off nginx version number displayed, add the following line to /etc/nginx/conf.d/default.conf file.server_tokens off
To control the Buffer overflow attacks, add the following command to /etc/nginx/nginx.conf file.## Start: Size Limits & Buffer Overflows ## client_body_buffer_size 1K; client_header_buffer_size 1k; client_max_body_size 1k; large_client_header_buffers 2 1k; ## END: Size Limits & Buffer Overflows ##
client_body_buffer_size 1k − This directive specifies the client request body buffer size.
client_header_buffer_size 1k − This Directive sets the headerbuffer size for the request header from client.
client_max_body_size 1k − It indicates by the line Content-Length in the header request.
large_client_header_buffers 2 1k − This directive assigns the maximum number and size of buffers for large headers to read from client request.Nginx and PHP Security Tips
To add security tips in php, it should require a file called chúng tôi The sample of chúng tôi file should be like this –[PHP] ;;;;;;;;;;;;;;;;;;; ; About chúng tôi ; ;;;;;;;;;;;;;;;;;;; ; PHP's initialization file, generally called chúng tôi is responsible for ; configuring many of the aspects of PHP's behavior. ; PHP attempts to find and load this configuration from a number of locations. ; The following is a summary of its search order: ; 1. SAPI module specific location. ; 2. The PHPRC environment variable. (As of PHP 5.2.0) ; 3. A number of predefined registry keys on Windows (As of PHP 5.2.0) ; 4. Current working directory (except CLI) ; 5. The web server's directory (for SAPI modules), or directory of PHP ; (otherwise in Windows) ; 6. The directory from the --with-config-file-path compile time option, or the ; Windows directory (C:windows or C:winnt) ; See the PHP docs for more specific information.
To disallow dangerous functions in PHP, add the following command to chúng tôi file.disable_functions = phpinfo, system, mail, exec
To set the maximum execution time of each script, add the following command to chúng tôi file.max_execution_time = 30
To set the maximum amount of time, each script may spend parsing request data. Add the following command to chúng tôi file.max_input_time = 60
To set maximum amount of memory for a script to be consumed, add the following command to chúng tôi file.memory_limit = 8M
To set the maximum size of POST data that PHP will accept, add the following command to chúng tôi file.post_max_size = 8M
To set maximum allowed size for uploaded files,add the following command to chúng tôi file.upload_max_filesize = 2M
Do not expose PHP error messages to external users,add the following command to chúng tôi file.display_errors = Off
To turn on safe mode,add the following command to chúng tôi file.safe_mode = On
To set limit external access to PHP environment,add the following command to chúng tôi file.safe_mode_allowed_env_vars = PHP_
To see all log errors,add the following command to chúng tôi file.log_errors = On
To set minimize allowable PHP post size,add the following command to chúng tôi file.post_max_size = 1K
To enable SQL safe mode,add the following command to chúng tôi file.sql.safe_mode = On
To avoid Opening remote files,add the following command to chúng tôi file.allow_url_fopen = Off
To upgrade Nginx, use the following command –$ sudo apt-get upgrade nginx
The sample output should be like this –Reading package lists... Done Building dependency tree Reading state information... Done Calculating upgrade... Done The following packages were automatically installed and are no longer required: libhdb9-heimdal libkdc2-heimdal libntdb1 python-ntdb Use 'apt-get autoremove' to remove them. The following NEW packages will be installed: nginx nginx-common nginx-core 0 upgraded, 3 newly installed, 0 to remove and 0 not upgraded. Need to get 349 kB of archives. After this operation, 1,297 kB of additional disk space will be used. Do you want to continue? [Y/n] y .....................................................................
After this article, you will be able to understand what is Nginx WebServer and how to secure Nginx WebServer. In our next articles, we will come up with more Linux based tricks and tips. Keep reading!
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