Version 15.1 by Erik Bakker on 2022/06/10 08:38

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2 = Running peer reviews inside eMagiz DevOps team =
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4 In this microlearning, we will take a look at peer reviews for eMagiz.
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6 Should you have any questions, please contact [[academy@emagiz.com>>mailto:academy@emagiz.com]].
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8 * Last update: April 22nd, 2021
9 * Required reading time: 8 minutes
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11 == 1. Prerequisites ==
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13 * Basic knowledge of the eMagiz platform
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15 == 2. Key concepts ==
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17 Peer reviews are defined as follows: A disciplined engineering practice for detecting and correcting defects in software artifacts and preventing their leakage into production. Its a well known and working concept with IT organization, and it can definetely applied in DevOps teams that have eMagiz as one of the technology pillars. In tbe context of eMagiz, peer reviews are done usually after the Create phase.
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19 [[image:Main.Images.Microlearning.WebHome@intermediate-devops-perspectives-peerreview-1.png]]
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21 Key benefits of peer reviews
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23 * Improved quality of integrations
24 * Higher consistency
25 * Knowledge sharing
26 * Keeping standards for optimal maintenance
27 * Architecture challenge and verification
28 * Find alternative solutions
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30
31
32 == 3. Running peer reviews in eMagiz ==
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34 === 3.1 Considerations for reviewee ===
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36 Here are some things to keep in mind when presenting the work to peer review.
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38 * Quickly explain the story / task / background
39 * Quickly show the working result if applicable / practical
40 * Talk through the solution while showing the models / code
41 * Just trying to explain your work to someone else will help spot mistakes
42 * Don’t show every single detail but try to highlight the important parts and/or details you’re less sure about. This takes time and experience to get “right” and is different depending on the story, the reviewee, the reviewer, the project, etc.
43 * Always do a peer review, no exceptions. Making assumptions about the usefulness beforehand defeats the whole purpose.
44
45 === 3.2 Considerations for reviewer ===
46
47 Here are some things to keep in mind when peer reviewing the work .
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49 * Ask questions
50 * How does this work?
51 * Why did you decide to …?
52 * Did you think about …?
53 * Spot (incorrect) assumptions
54 * Check application of best practices – see next slide
55 * Modelling / coding patterns
56 * Naming conventions
57 * Errors / warnings
58 * Notice non-standard / unusual / abnormal things
59 * Make sure this is documented, mainly for future changes. Annotations are very useful here.
60
61 === 3.3 Peer review items per ILM Phase ===
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63 * Capture
64 * 100% filled
65 * Connection method clear
66 * Authentication method clear
67 * Definitions loaded
68 * Sizing impact understood and valid
69 * Design
70 * Check solution architecture validity
71 * Design 100% filled and clear
72 * CDM Root entity mapped
73 * Set as mapped – avoid line mapping
74 * Use annotation where possible
75 * Proper flow and system settings
76 * Create
77 * Validate routing
78 * Generic error response flows
79 * Check naming conventions flows, properties and XSD
80 * Split messages in on-ramp – not later
81 * Deploy
82 * Check properties
83 * Avoid too many different flow versions – max. 2
84 * Remove test packages that are deployed
85 * Manage
86 * All alerts mapped to Customer Support
87 * All messages can be explained
88 * Avoid code mappings
89 * Enable default alerts
90 * Architecture
91 * Deploy connector close to the source/target system
92 * Ensure ACCP and PROD are exact copies
93 * Cloud over on-premise
94 * No hard-coded variable – use properties
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96
97
98 == 4. Assignment ==
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100 See how peer reviews are currently implemented within the projects on which you work to see if you can learn something from the information you have gathered via this microlearning.
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102 == 5. Key takeaways ==
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104 Peer reviews are instrumental in any DevOps team. Use the provided list as your team's peer review starting point and tune as you go along.
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106
107
108 == 6. Suggested Additional Readings ==
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110 You will find plenty background items available on the Internet.
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112 == 7. Silent demonstration video ==
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114 As this is a more theoretical microlearning we have no video for this.
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